SAP Cloud Platform: Everything that your Enterprise must know

To begin with, SAP Cloud Platform is a leading platform, crafted as a service for building brand-new applications in a secure cloud computing environment by SAP. Moreover, it is also a platform for propagating existing applications managed by SAP. So, the SAP Cloud Platform merges seamless business procedures and data.

However, SAP changed its ERP software strategy with the advent of SAP S/4HANA and SAP HANA database in the early 2010s. In 2016, after the release of SAP S/4HANA cloud, the entire SAP HANA cloud platform was transformed to SAP Cloud Platform in 2017. So, the article will let you know everything that your enterprise shouldn’t miss out on! Let’s get started!

What are the SAP Cloud Platform licensing models?

It is available mainly in two commercial models, which are consumption-based and subscription-based. According to SAP, these two crucial options allow organizations a flexible way to match SAP Cloud Platform services with the company’s needs.

Success Case: SAP S/4 HANA Implementation On Cloud: Machinery Manufacturing Company

Under this premium subscription model, customers can get quick access to SCP services for a specific range of time and a fixed price. Here, the enterprises can utilize as many of the services as they need. Therefore, the model allows companies to safeguard their exclusive IT investments with known costs considering they are subscribed to the service.

On the other hand, under this central consumption model, clients can purchase SAP Cloud Platform (SCP) services via credits and utilize them to understand their fitness. However, such a significant setup enables organizations to inaugurate and scale up development projects instantaneously whenever the business requirements have changed.

Those SCP credits are generally paid for upfront, and an entire cloud credit balance is sustained for the usage of all premium services.

Establishing SAP HANA Cloud from the SAP Cloud Platform Cockpit

In order to start establishing your SCP account, you will have to get started with the SCP cockpit. No idea of what it is? Let us tell.

What is SAP Cloud Platform Cockpit?

The SCP Cockpit is a premium web-based interface, mainly used to work with the major SAP cloud applications, e.g. HANA Cloud. Now, you can effectively operate your SCP account and build quick instances whenever required.

Your organizational account on SCP is your global account. So, if you are the SAP admin of your enterprise, you will get complete control over your account and also be capable of creating spaces, subaccounts, and leading instances.

Also Read: Why is it Essential for You to Migrate to SAP S/4HANA Right Now?

In brief, if that global account represents your whole company, the sub-accounts might be those specified departments and also the geographical locations. However, it will solely depend on the company’s internal structure.

SAP Cloud Solutions

SAP has implemented two bifurcated strategies to develop its suite of cloud solutions. While others have been incorporated into its portfolio via a belligerent acquisitions strategy, it has diligently created specific in-house solutions.

●  SAP Ariba

It is a comprehensive collection of major applications that operate several procurement activities. These include contact and invoice management, supplier collaboration, and spend assessment. However, it was previously launched as an internet-based procurement tool in 2012, independent of SAP.

●  SAP Concur

It is one of the best travel and expenditure management tools that the employees can use to book business travel effectively. So, your enterprise can get paid back for those incurred expenses and non-compensation-oriented finances.

●  SAP Customer Experience

SAP extraordinary customer experience is the best suite of solutions, which contains five exclusive cloud applications. These are SAP service cloud, SAP commerce cloud, SAP marketing cloud, SAP customer data cloud, and SAP sales cloud.

Also Read: Dynatrace for SAP Hybris – The Arrival of the Commerce Cloud Monitoring Age

Additional definitions of SAP Cloud Platforms

According to the information mentioned earlier, there are many crucial SAP Cloud Platforms terms you must be aware of! Here, these are listed below:

●  On-premise

It means installing an outstanding SAP solution, which is physically introduced at the customer’s property. However, this is a complete opposite of a cloud solution.

●  SAP API Management

It is an entire lifecycle application programming interface (API) platform previously identified as SAP Cloud Platform API Management.

●  Hybrid deployment

The SAP solution installation consists of both cloud elements and on-premise elements. Moreover, it is referred to as a prominent “two-tier architecture.”

●  SAP Cloud Application Lifecycle Management

SAP uses one of the best administrative tools for their customers, harnessing cloud solutions to safeguard their solutions secured and up-to-date.

SAP Cloud Platform services and capabilities

The premium SAP Cloud Platform services offer a wide array of capabilities and services. SAP has listed a total of 19 capabilities in August month of 2018. All these fall under data-oriented analytics, services, user-based activities, developing technologies, and application deployment and development. However, the significant competencies include the following:

  • Mobile that allows mobile app development.
  • Analytics enable you to incorporate modern analytics into applications for authentic results.
  • User experience, which allows enterprises to develop customized and hassle-free user interactions.
  • DevOps helps facilitate application operations and development.
  • The integration lets you combine cloud applications and on-premise applications.

Also Read: S/4HANA Upgrade (Technical, Functional upgrade and Fiori upgrade)


SAP Cloud Platform is one of SAP’s creative cloud deployment and development platforms operating on several cloud infrastructure providers. Moreover, SAP API Management allows companies to reveal their information and procedures as extraordinary application programming interfaces (APIs).

This premium solution again aids in operating such APIs based on lifecycle and governance. On the other hand, this superior multi-cloud foundation upholds environments, for example, ABAP, Cloud Foundry, and Kyma, along with the multitude of diverse regions and distinction of choices of programming languages.

In brief, SCP is a top-notch platform that allows partners and customers to propagate their existing applications, hence creating those practical applications that can deliver elevating competencies.

If your enterprise is thinking to add it to the IT infrastructure of the organization, it is indeed the wise move. However, make sure to hire SAP Cloud experts to leverage the most out of it.

Augmented Analytics and which top BI tools will suit the best for your Enterprise?

Augmented Analytics has changed the way of contemplating analytics and data due to its subtle blend of two emerging technologies, analytics and AI. The rising future of all the business intelligence tools (BI) can provide the crucial features so that users can gain various insights into understanding those features.

The best-in-class feature of the BI tools is to utilize augmented analytics. These tools change the unprocessed data into actionable and purposeful insights. More precisely, such tools assess the characteristics of the data and transform those analytical and presentable data sets into dashboards and reports.

Due to the enormous data challenging situation in businesses, no matter what the size is, ensuring seamless business procedures tend to get more complicated every year. That’s why companies require specific help in terms of making profitable and sustainable decisions.

By leveraging professional and advanced BI tools, every issue can be promptly identified without any requirements for primary IT intervention. Today’s article will check out the vital augmented analytics features in the top 4 BI tools. Let’s get started!

Why is Augmented Analytics the future of BI?

Before digging deeper, you should know the reason first! Let’s take an insightful look at the probable reasons for adopting such technology.

1.     Rapid decision-making

Augmented analytics helps you find the datasets for their inclusion in evaluation, suggest some original datasets, and warn users while updating datasets. So, when the users don’t get anticipated results, augmented analytics help you find some datasets. Users can expect to gain precise predictions in terms of historical data with just a click.

2.     Data Democratization

It ensures data availability to every user! Augmented Analytics offers seamless algorithms and prebuilt structures. That’s why organizations don’t require IT specialists to accomplish such work. Moreover, such models have superior user-friendly interfaces to ease the work of executives when they want to use the BI tools.

Augmented Analytics features in top 4 BI tools

The analytics features of the top 4 BI tools are shown below:

Power BI

  • Flexible titles
  • Building business on safeguarded data analytics
  • Data loss prevention
  • BYOK features
  • Safeguard organizational data with Power Bi security with service tags


  • Domo Appstore is a leading ecosystem of dashboards, pre-built apps, and connector APIs
  • You don’t need to learn SQL when you utilize its magic ETL feature
  • It offers automatically recommended visualizations
  • Users can connect over 1000 pre-built cloud connectors


  • Powerful sharing and collaboration
  • Tableau dashboard offers an entire view of your datasets through texts, visualizations, and visual objects
  • Powerful security
  • In-memory and live data
  • Seamless mobile view


  • Scalability and mobility
  • Quick application development
  • Data exploration and natural analytics

Now, let’s talk about each of these tools in a bit more detail:

1.    Power BI

The supreme ML capabilities and the availability of up-to-date features of augmented analytics make Power BI the most proficient in its analytical competencies. It has seamlessly integrated top-notch AI functionalities in Q&A visuals and Quick Insights. These can assist users in assessing and fathoming the data rapidly.


  • Enticing visualization options are available
  • Users can make confident decisions
  • It maximizes business productivity
  • A better understanding of business insights
  • The desktop version of Power Bi is free of cost
  • Anyone can use it due to its non-technical features
  • A wide array of graphics and visuals are in the Power BI tool
  • Users can avail of a transparent notion of Excel data based on reports


  • Users should possess a license or a Microsoft environment to work on
  • It’s PRO plan charges $9.99/month/user, but it’s premium version is a bit pricey

2.    Domo

Domo is one of the complete BI solutions consisting of myriad systems showcased in this platform. It starts with data connection and integration. Such an outstanding BI solution gets finished with propagated data with custom apps fetched from the Domo Appstore. Utilization of Domo could be in:

  • ETL tools
  • Data lakes
  • Warehouses
  • R or Python scripts

That’s why users can prepare their datasets for predictive modeling with the aforementioned factors.


  • Intuitive user interface
  • Seamless communication capacity among the users
  • Analyze organizational data at any time
  • Flexible BI tool, which can be fitted in a wide array of use case scenarios


  • Expensive BI tool
  • Building out custom reports often take time

3.    Tableau

This BI software helps anyone to get connected to data in just a few clicks. This is how users can create interactively, visualized, and shareable dashboards with Tableau. It plans to combine Einstein analytics in a fleet swing after proclaiming that the whole salesforce Einstein Analytics got congregated with Tableau.

Its features like Explain Data and Ask Data demonstrate that the business is moving forward to the conventional visualization-worthy tools.


  • Rapidly proves or refutes hypotheses about various operational terms, which propel outstanding data trends
  • Quick prototyping
  • Amazing repository of gaining knowledge about materials online
  • Easy to understand and utilize


  • Cumbersome to merge with code environments
  • Inadequate support

4.    Qlik

Qlik provides its users with a top-notch and high-performance associative engine, which is helpful for any proficient user to search and discover all the significant datasets. It upholds valuable data exploration harnessing its premium augmented analytics feature.

It includes Insight Advisor, which can boost the data preparation process, automates it, and generates auto insights by assessing the data. Also, its extraordinary feature of Insight Advisor helps support natural language interactions.

In brief, users can build, improve, and customize data utilizing Qlik’s data preparation and accelerated creation.


  • Hassle-free data sharing
  • No maintenance required
  • Amazing data delivery speed
  • Cost is moderate


  • Poor customer support
  • RAM limit is less

Concluding words

Augmented analysis is a leading part of every BI tool due to the colossal volume of data generation. That’s what makes the BI tools a robust and flexible resource for various companies.

To leverage from augmented analytics, you should opt for the top-notch BI tools for your company by considering the factors like data volume, surroundings, and scalability for the long run. Hopefully, you have acquired the best knowledge from our detailed and insightful description of features of every business intelligence tool.

For the deployment of any of the Business Intelligence tool for your enterprise, consult with experts at Stridely Solutions or take our services any time.

10+ RPA and Machine Learning Use Cases that might Interest your Enterprise

Cutting-edge technologies, including AI, could immensely aid enterprises in disclosing engagement, productivity, and hardware collaboration with powerful and smart automation, RPA, and predictive ML. AI could be identified as the leading science of imitating human behavior.

ML is the substantial subset of AI, which helps train a machine to learn everything about it. Therefore, by combining ML with AI into the Robotic Process Automation (RPA), anyone can seamlessly perform smart and advanced automation of repetitive tasks and countless operations with layers of judgment, human perception, and prediction.

However, RPA has brought great benefits to enterprises. We have previously discussed RPA, and if you are wondering “what RPA is in simple terms,” this article contains all the answers. Furthermore, AI, ML, big data analytics are all on their way to usher an advanced era into the industry.

So, without further ado, let’s check out the best use cases of RPA, ML, and a few of RPA & ML.

Also Read: Entering the Decade of Automation – RPA for All

4 Best use cases of Robotic Process Automation (RPA)

Marketing: Lead Generation

Lead generation is an inevitable part of nowadays seamless marketing processes. The professional marketing team makes brand new entries for prospective leads within a CRM system amassed from outside sources. On the other hand, the majority of CRM platforms provide their self-built-in data upload tools.

Various legacy platforms are there, which need users to provide each brand new lead’s information. This is how shortening the time staff and enhancing the probability for error. With Robotics Process Automation (RPA), users can easily program the software to take the data from their spreadsheets.

Success Case: Automating Business-Critical Processes Via Next-Gen RPA Solutions

The employees of any enterprise can focus on getting associated with lead prospects rather than data entry to provide faster and accurate results.

Processing faster refunds

The reputation of any enterprise relies on how quickly it can solve the issues and refunds. Consumers call for this process to be faster, seamless, and pain-free! Hence, it is much more hassle-free.

Return requests and complaints produce much more data, which could be full of challenges while sorting through. RPA deal with those procedures and matters, which can refund without any significant delay. Therefore, ennobling customer satisfaction and possessing an optimistic impact on your brand’s reputation.


It will be a time-consuming, hectic, and repetitive task to process payroll every month for a team in your organization. Hence, it includes a significant amount of data entry. Employee dissatisfaction stems from data inaccuracy in payment.

So, it would be necessary to consider the payroll use case. RPA crosschecks employee data consistency throughout numerous systems, loads earnings, verifying timesheets and tax deductions.

Also Read: RPA: A Blessing in Disguise for Accounting & Finance Industry

Here, virtual robots can administer taxable advantages, automate salary slips and other major paychecks. In brief, RPA automates payroll-oriented transactions to evade impreciseness, delays, and other hassles.

Price Comparison

Businesses need to make bulk purchases in order to provide top-notch services or manufacture quality products. Therefore, the price of such items has a profound impact on the enterprise’s revenue or profits. However, employees of any organization keep on researching online to offer knowledge-based and cost-cutting decisions.

Furthermore, researching is a complex and time-consuming process; that’s why we can observe it as diverse RPA use cases in various enterprises. So, it can be seen that chatbots make a thorough comparison of prices from diverse vendors by their high-rated product attributes. After that, businesses can purchase superior products at the most competitive rates.

Best 5 Use Cases of Machine Learning (ML)

Sales Optimization

Sales usually produce colossal unstructured data, usually utilized to give proper training to the ML algorithms. It could be a piece of fantastic news for the enterprises, which have been keeping customer data for several years.

The companies that are inclined to achieve a highly competitive edge are nowadays applying machine learning to both sales and marketing challenges to complete strategic objectives. Top-notch marketing strategies count on ML models, including ad placement, creative content, and predictive lead scoring.

That’s why by adopting ML in organizational activities, they can quickly grow and customize content to fulfill the ever-changing requirements for potential customers. Moreover, these models are using primarily for sales forecasting evaluation, consumer sentiment assessment, and customer churn conjecture.

Also Read: RPA is like the Band-aid Feature for the Future


ML diligently helps organizations optimize their threat assessment and also how they can simultaneously respond to security concerns and attacks. According to the ABI research analysts, ML in data protection will enhance to $96 billion by 2021.

Furthermore, ML makes it hassle-free to analyze truckloads of data logs from IoT and mobile devices. So, it can produce variable profiles for behavioral patterns along with your IoT systems. However, the companies that accept a risk-aware characteristic are in a fantastic position to sustain a leading position in their industries.

Customer Service

Virtual digital assistants and chatbots are the new future of this era, ruling the world of customer service. Because of enormous customer interaction volumes, the colossal data are now being captured and assessed every day in order to fine-tune machine learning algorithms.

On the other hand, adopting ML in the company cloud could possess an impeccable impact on executing customer service-oriented routine tasks. However, as per the PWC report of 2017, approx 31% of the decision-makers of any company displayed the major impact of virtual personal assistants on solving the needs of their customers.

At the same time, 34% of executives reported that using chatbots was helpful for them to channel their contemplation towards profound creativity.

Process Automation

The Intelligent Process Automation (IPA) blends automation and AI. Hence, it showcases the distinct usage of ML. Such use cases list starting from automating manual data entry to more complicated automating insurance risk evaluations.

All thanks to its cognitive technology, such as machine vision, natural language processing, and deep learning. Here, machines can ameliorate conventional rule-oriented overtime and automation in order to adapt to the changes.

Also Read: Business Era: IoT, Bigdata and Machine Learning

Moreover, the enterprise benefits are much more than cost savings. Also, it includes superior usage of pricey equipment, quicker decisions, service, actions, and proficient employees. This is how ML in the enterprise liberates staff to focus more on service development and product innovation.


The leading criteria to adapting the maximum of the ML in the organization lies in the competencies of both human intelligence and ML.

Therefore, such premium collaboration tools possess much more potential to enhance effectiveness, fleet the new ideas’ discovery process, and optimize teams’ optimized consequences, who can collaborate from remote locations.

Some top-notch use cases in the collaboration space contain integration of chatbots, video, audio, image intelligence, and real-time language translation.

Also Read: Implementing IoT and AI for your Business – Beat your rivals Efficiently

Top 4 Use cases of both RPA and ML


Cybersecurity professionals have worked passionately and hard enough to respond to the continuously rising spectrum of security menaces as networks are gradually becoming highly complicated. It’s primarily complicated and challenging to impede hacking techniques. However, the evolution of IoT devices has amazingly transformed cybersecurity. This is how an enterprise can be susceptible to threats and malware.

Luckily, ML algorithms have triggered cybersecurity actions to sustain such quick developments. More precisely, predictive analysis has shown a lower number of hazards and quick detection than ever before. RPA and ML can now assess user activity amid a network to identify security issues, malware, and other threats.

Process Assessment

Process analysis has been performing quite often for decades by top-notch consultancies. Hence, it is the most amazing business-critical initiative have ever taken by anyone! Consultants prepared the process flow diagrams and interviewed several businessmen to assess and map their daily activities.

ML helps a lot to quickly evaluate process data in terms of system logs, user activities and identify repetitive structures. Hence, it mirrors the scopes for process automation and optimization. More importantly, the discovery bot is a top-notch example of an automating process assessment solution.

Fraud Identification

Today’s modern world is based on online financial transactions. Therefore, this has also loomed customer awareness of numerous fraud types. Customers appreciate the seamless online transaction facility. However, at the same time, they are worried about the safety norms. That’s why credit card enterprises harness ML algorithms to assess maximum volumes of transactional data to ascertain skeptical behavior.

Moreover, such kind of checking processes and following guidelines are not new; ML has drastically improved the function and scope, unbolting up to 95% of fraudulent activities and shortening investigation time by 70%. As per the example of RPA solutions benefitting fraud identification models manufactured with Google AutoML.

Claims verification and processing time for insurance industry

Continuous complaints have been coming forward from the insurance industry because of the time-consuming procedures during claim verification and processing time. Here RPA allows insurance organizations to crosscheck claims harnessing predefined regulations and reduce fraud claims.

On the other hand, in order to streamline claims processing time, RPA enhances the processing speed and enhances the customer experience. Previously, the manual processing claims demanded a plethora of time because of data extraction and adding data into those forms.

Concluding words

In a nutshell, today’s fast pace era calls for robotic process automation and machine learning. Whether it’s to minimize budgets or optimize your operational effectiveness, RPA has become a significant necessity for all types of enterprises and there are much more use cases to arrive. The breadth of use cases and major applications for RPA and ML will propagate in the upcoming years as the gradual advancement of technology will happen.

In this new beginning of the era, it becomes inevitable to utilize ML applications for saving budgets, optimizing productivity, and propelling enterprises towards development.

You may start small to ascertain if it is appropriate choice for an enterprise, and thereafter or automate your whole enterprise gradually. Stridely Solutions has a reliable team of RPA experts that could consult you and provide needed services as and when needed.

Your Guide to SAP Business One for Manufacturing

Regardless of the business’s size and nature, owning an ERP Implementation is a must. This one tool can streamline tons of business fronts and enhance business productivity. Those who are looking for a comprehensive, cost-effective, and centralized ERP solution must consider SAP Business One.

From accounting to CRM, SAP Business One is capable to empower every crucial frontage. In this guide, we’re going to educate you on the nitty-gritty of SAP Business One. Whatever one needs to know about this powerful business tool is covered in this guide.

Also Read: SAP Business One for Chemical Manufacturing Industry

Referring to it beforehand will resolve loads of doubts and queries. Implementation and usages of SAP Business One will become a lot more effective and result-oriented afterward.

SAP Business One – Know about this true Game Changer

SAP Business One is a high-end ERP platform intentionally designed for small and mid-size businesses helping them to streamline the key processes, gain real-time insights into the business operations, and make data-driven decisions.

It comes with notable business intelligence and SAP HANA integration to empower the operations. Since its development, SAP Business One is updating to meet the current industry needs. Presently, there is SAP Business One 10.0 version was launched which features cutting-edge Microsoft Office 365 integration and analytics charting capabilities.

After this upgrade, SAP Business One has become a bit more lucrative. Speaking of the deployment options available, SAP Business One is going a commendable job as:

One can get its cloud deployment subscription which asks for a monthly license fee to offer all of its features. This deployment option is quick, hassle-free, and can be at your service without asking for any in-house IT assistance.

Its on-premise deployment is available granting direct control of the ERP data. With this deployment option, one can enjoy flexible reporting and internal security policies.

Users have the facility to enjoy high-end ERP capabilities from their mobile with the SAP Business One mobile app. It’s an on-the-go solution granting maximum productivity to businesses.

Key SAP Business One Modules

As there are an array of business needs, SAP Business One offers different kinds of modules to address all kinds of needs. These modules are designed to keep various business areas and can be managed on a single interface. The key SAP Business modules come in administration, resources, sales, banking, sales, inventory, financials, business partners, reports, HR, MRP, service management, project management, and production management.

Also Read: SAP B1 Implementation For Pharmaceutical And Healthcare Manufacturing Unit

SAP Business One is here to help at every business front. There is more to it. If certain needs fall out of the periphery of these modules, SAP Business One is flexible enough to customize the solution just as the business requires.

Which Are the Ideal Users of SAP Business One?

We have understood what SAP Business One means. Now, it’s time to figure out who all can use it to leverage their business productivity. The decision of replacing the existing ERP system with SAP Business One depends on multiple factors. Such as:

The current accounting package fails catering the business needs and functionalities.

  • Business is still running on outdated spreadsheets
  • Absence of a centralized information exchange platform
  • Lack of automation in the menial and repetitive tasks
  • The old ERP system lacks continuity and lack of support

Organizations with employee strength of 10-100+ with $10 + million turnovers can use SAP Business One without any qualms. Its adoption is not limited to this organizational structure as multinational companies with a motive to streamline the effective branch and entities management can also use this tool to empower their operations.

SAP Business One for Manufacturing

The manufacturing industry is highly challenging as it requires proper supply and demand management. One has to keep track of the project, raw material purchased, timely delivery of project, and the like business goals. Ensuring all of this and many other factors becomes a daunting task as manufacturing industry operations are disturbed by many external factors like:

  • Raw material price change and its shortage
  • Long lead time from an overseas supplier
  • Improper project scheduling
  • Ineffective management of resources and raw materials

Gladly, introducing SAP Business One can curb all these and many other hurdles in a blink of an eye.

Perks of Implementation of SAP Business One

Using SAP Business One will improve the functionality of all kinds of businesses. For the manufacturing industry, this is what one can expect after SAP Business One implementation:

●  Time-bound deliveries – With real-time tracking, scheduling, and optimization of each of the project-crucial aspects like availability of staff & resources, in-transit raw material delivery times, lead times, and project progress, SAP Business One ensures that no project remains overdue.

●  Effective resource planning – With SAP Business One, it’s possible to manage the labor, machinery, and resources as per the demand of a specific project. Wastage can be prevented.

●  Full inventor control – SAP Business One is designed to trace the batch & serial number, landed cost, check the stock levels, auto-order the finished raw material, and measure the materials in multiple units. In short, there will be full control over the inventory.

Key Features To Watch Out While Utilizing SAP Business One for Manufacturing Industry

The above-mentioned benefits can only be fetched if the at-service SAP Business One for the manufacturing industry has enough supportive features. Here are some of the top-notch features that should be a part of SAP Business One while you’re utilizing it for the manufacturing industry.

● Project & Production Management – This is a must-have feature if, as a business, one wants to stay on top of the projects by performing real-time and cross-functional reporting. This feature makes logistics management, cost accounting, controlling, and project scheduling-related tasks a lot more simplified.

● Material Resource Planning (MRP) II & Production – Array of materials and resources are used in the manufacturing industry. For proper cost optimization, the effective management of material and resources is a must. This feature does this job with utmost perfection as order & stocks records can be auto-updated, end-to-end production controls can be gained, and mixed & variant production can be handled.

●  Dashboard – Get a 360-degree view of the business operations, have a detailed analysis of the key operations, and become more aware of the team functionalities as SAP Business One offers a highly customized dashboard to the end-user. With the help of this dashboard, it’s easier to have enhanced operative reporting with flexible ad-hoc queries.

●  Quality Controls – Quality is assured at various stages in the manufacturing industry. With the help of this feature, it’s easier to execute the quality tests during the material flow. The quality testing can be implemented from the early procurement stage and can be done till the project ends.

●  Cost Estimate – Create accurate and apt project cost with this feature. This feature can generate real-time estimates for the products/projects and can generate quotations for custom manufacturing orders. Based upon each entry, the profit margins can be auto-calculated allowing businesses to have a detailed overview of the future outcome of a project.

●  Advanced Planning and Scheduling (APS) – This feature is bliss for the manufacturing industry as it ensures timely project delivery, Using this feature, one can easily view order times, lead times, capacity allocations, transition periods, stage of the project completion, availability of resources, and bills of materials. Delays in operational level can be spotted early with the help of this feature.

●  Multiple Warehouse Management – Utterly optimized inventory management with facilities like tracking of remaining stock, updating the raw material price, placing the orders for out-of-stock raw material, and bin location tracking, this feature will make warehouse management an easy task.

●  Product Configurator – Use this feature to do proper management of multiple variants of the same product.

It’s not always blissful!

Just like any other thing, SAP Business One also comes with a fair share of pros and cons. Pros have been discussed above. Let’s learn about its cons.

  • SAP Business One, as quoted above, is handling tons of things at a time. Because of this, the initial configuration and setup are not a piece of cake. For an organization lacking enough technical cognizance, it could be too daunting. This is why – most of the time, there is a need for an SAP Business One implementation partner or a Value Added Reseller. In each case, spending some extra bucks is a sure thing.
  • When it comes to browser extension compatibility, it lacks credibility. Officially, it works only in the Mozilla Firefox browser. Chrome is not supported which is a huge negative point. Even the Mozilla Firefox extension has poor functionality. There are tons of complaints about its incompetency.
  • We figured out its ancillary system application like HR lags behind in terms of features.
  • It feels good to hear that SAP Business One supports extensive customization. But when it comes to reality, this sort of complex customization can become a headache for few. Businesses with limited functionalities can find it too cumbersome to work with.

The Final Say

SAP Business One is a cut-above business tool that everyone can bank upon blindly. For the manufacturing industry, this is just another way to leverage productivity, ensure timely project delivery, and keep the expense under control. Hence, if your old-school ERP need is pending for update or you haven’t integrated any ERP system in your manufacturing industry-related business, think of SAP Business One deployment with Stridely Solutions soon.

Accelerating business transformation with Dynamics 365 and Microsoft Power Platform – How can you do that?

All through these years, Microsoft Dynamics 365 and Microsoft Power Platform have earned notable significance as these two tools can effectively break- down barriers, leverage team’s productivity, help a business to adapt to the rapidly changing technologies, and innovate as per the business needs. The notable fact is that these benefits can be availed all across the industries.

No wonder why these two platforms are creating history with each passing day and continue to grow without any restrictions. Dynamics 365 experienced 45% of growth in Q3 while Power Platform is becoming the future of the business process automation. Nearly, 16 million active users take the help of this platform to automate the mundane processes, do data analysis, design a business-focused app, and set up a virtual agent.

Also Read: An all-inclusive View of Dynamics 365 and how it helps in Boosting Digital Selling

When digital transformation is an aim, these two tools are going to bear the majority of the burden and responsibilities. In this post, we will try to figure out how these two resources can address the business transformation challenges, support the businesses during digital transformation, and make them time-relevant.

Business Transformation – A Quick Overview

Change is evident. With time, certain processes, technologies, and business methodologies become obsolete. Maintaining pace with these changes and taking appropriate steps is necessary to the survival of a business. This is where business transformation comes into the picture.

This is the process of adopting new or upgrading existing processes and technologies with the purpose of improving efficiency, capacity, and ROI. It is a form of change management strategy bring into practice with proper alignment of people, processes, and technology as per the changing times.

The essence of business transformation is based on the three “T”s.

The first T stands for Team and refers to the people who are responsible for handling the business transformation of a given ecosystem. The ideal business transformation team features some of the key in-house pros who are aware of the organizational needs and a few highly professional outsourced technicians.

Tools are the second crucial T and refer to the new tools that need to be a part of the business ecosystem during the transformation journey. Make sure these tools have been deciding after figuring out the needs of the ecosystem. For system, if a business has struggled in managing the CRM in the past, a high-end CRM system should be part of the future business transformation strategy.

The last T refers to timelines. Business transformation can last for few days or few weeks, depending upon the work done and changes made. It’s essential to set a timeline before embarking on a business transformation journey. In its absence, one will fail big time to achieve the goals and attain perfection in this process.

Digital Transformation Is At the Pivot of Business Transformation

Business transformation happens at multiple faces. Digital transformation holds the highest merit. No business transformation is complete or makes sense if digital transformation is not done.

Tech Pro Research was surveyed in 2018 and figured out that nearly 70% of companies have already designed a digital transformation strategy or working towards it. Things haven’t changed much since 2018. The growing involvement and penetration of technology have only augmented the need to be digitally sound.

We have already told that business transformation happen using systems, people, and technologies. All these activities are the key elements of digital transformation and can’t be achieved in its absence.

Using Microsoft Dynamics 365 and Microsoft Power Platform for Impactful Business Transformation

For MSPs and other businesses, seeking business and digital transformation, Microsoft 365 and Microsoft Power Platform is the gateway. Both these tools are capable to deliver a highly customized and high-end suite for collaboration, productivity, and communication operations that can easily satisfy the generic and aforementioned business transformation requirements.

Also Read: Power Platform Utilization for Business Process

Microsoft Dynamics 365 features a bunch of business intelligent applications that can help a business to streamline operations, deliver greater results, and provide AI-driven insights.

Similarly, Microsoft Power Platform is a term used for a collection of solutions like Power BI, Power Virtual Agent, Power Apps, and Power Automate.

As a whole, these products are used for manipulation, automation, and analyses of data, along with other substantial products like Office 365 or Dynamics 365. Not only the Microsoft apps and products are compatible with Power Platform, but tons of various other third-party apps can also be integrated effortlessly with this amazing tool.

Also Read: Office 365- Shows more ways to be Productive

In conjecture to each other, these two technologies can leverage the business transformation journey of any sort of business. Here is why we are stating this:

  • Cut down the time consumed

The time that one has to devote to transform that business at every stage is usually on the higher side. The larger the organization’s size, the time consumed by the business transformation will be higher.

Gladly, the majority of the Microsoft Dynamics and Power Platform solutions follow the plug-and-play philosophy. The offered solutions or modules are segregated already and are offered as independent solutions.

One doesn’t have to spend hours after hours to figure out which one would be the best. For instance, Microsoft Dynamics 365 comes in

Dynamics 365 Customer Engagement – Sales, Service, Marketing and Customer Service, Dynamics 365 Customer Insights, and Dynamics 365 for Finance and Operations options. The functionalities and offerings of each module is already well defined.

Also Read: Dynamics 365 Customer Voice – What it is and what makes it good for your Organization?

Hence, taking up a decision won’t be a tough task. You need to transform the Enterprise CRM front, go get the Dynamics 365 Customer Engagement – Sales, Service, Marketing, and Customer Service. Wondering what should be done to streamline the financial front? Dynamics 365 for Finance and Operations is the right choice to make.

The same is true with Power Platform. Each offering has pre-defined functions and roles. Using the Power Apps, one can design mobile-friendly business apps and enhance the market reach.

Power BI is a cutting-edge BI tool designed for data analysis and creates success-driven business visuals. The same is applied to the rest of the solutions.

When there is so much clarity on which does what, there is no unwanted brainstorming and time wastage. Decisions regarding which tool or solution to be used and which to be dumped can be made quickly. This way, one can speed up the entire process of business transformation and save a huge deal of time.

  • Business transformation is now purpose-built

With a pre-designed solution, it’s not easy to achieve 100% satisfaction and viability during the business transformation because what might seem good for one ecosystem could be useless for another.

Both these tools and solutions are known for their high-end customization and flexibility.

Because of this, one can have purpose-built solutions. Whichever module or solution you pick from Microsoft Dynamics 365 and Power Platform, it can easily mingle with the existing systems or the systems which you don’t want to be part of the ongoing digital transformation.

It is superb when it comes to reducing the hassles involved in brings all the tools and solutions over a single platform and connect.

  • Unified experience across all the solutions

One of the most daunting tasks that business has to face during the business transformation is to maintain uniformity across the solutions.

Each one of the modules of these two technologies has been designed keeping a centralized theme in mind. Hence, there won’t be any issues on this front as well.

  • Easy interfaces

What makes a business, which has already started or going to embark on a business transformation journey, worried is having a great hold of the new or updated systems. Some of the team members can do good while few might need training.

This is bound to happen as no two team members have equal sense or competency. It is a huge hindrance in the business transformation as even if the process or implementation is done completely, this limited team member competency will prevent the functioning of new systems.

Regardless of the modules chosen, all of the Microsoft Dynamics 365 and Power Platform offerings are famed for an easy and user-friendly interface. Be it Power Apps or Dynamics 365 Customer Engagement, amazing user-friendliness is promised.

It saves a huge chunk of time that any organization has to invest in team training. The updated systems and solutions will be readily available for use.

Implement business transformation with strategic consulting

Business transformation, when done in the right manner, can be too daunting job as there are tons of aspects to look after. Some even fail to recognize the areas where transformation should be done. This is why it’s highly recommended to take the help of a professional and strategic business transformation consulting firm.

With strategic consulting, it’s easier to figure out which all areas need to be transformed, create a viable transformation plan, ensure proper implementation of the expansion strategy, and make most of the business transformation plan.

Also, a professional consulting and IT Services firm with rich experience in working with Microsoft’s technologies will allow a business to figure out which module, out of many, is worth investing in.

Conscious and smart business transformation decisions can be made with their help. So, don’t hold yourself. Embark a business transformation journey by having Microsoft Dynamics 365 and Microsoft Power Platform by your side.


Knowledge Discovery through Data Mining: Functioning, Techniques, Pros, Tools, Challenges & Use Cases

We live in the age of enormous data generation, where our all gadgets, services and platforms are creating footprints in digital world in form of data. Facebook alone processes around 500+ terabytes of data every day. This data is processed and the fetched information is sent to product owners, helping them build a better product or improve the current one.

The above-mentioned process of extracting useful information from an accumulation of data, and making sense of it, is called Data Mining.

Data Mining is useful for dozens of business verticals in various ways. If you want to figure out how it works and why it is valuable for you, this article will help you out. We also have covered data mining tools and use cases thoroughly for providing detailed insights.

Also watch: Process Mining – A Value Discovery for Enterprises

How Data Mining works?

Data mining tools utilize various statistical, mathematical, and analytical procedures to monitor and analyze the enormous amount of data. In fact, the technology proves to be more helpful and valuable with larger data sets and with more user experience.

The outputs of data mining processes are patterns, grouped/separated data sets, relationships in data, trends, predictions, and so on. Together (or alone), this information can help organization in decision-making and business planning.

Data mining operation consists of the following elements:

  • Define the Problem – Stakeholders should be know about internal & external data types that will be used for this exploration, alongside having figured out the problem area for this particular functional use case.
  • Data Gathering – Assess, collect and understand the required data from various sources.
  • Prepare & Pre-process – Extract the relevant data sets and cleanse the data as per requirement.
  • Data Model – Select the proper algorithm and build predictive models.
  • Train and Test – Train the data model with appropriate data and simulate.
  • Verify and Deploy – Verify final data model, prepare visualization and deploy.

Why use data mining?

Whenever you have to work with a plethora of data in real-time and despite having the task as essential, you think of it as unreasonable, data mining can be your savior.

The key benefit of data mining is to identify hidden patterns and associations in huge volumes of data from multiple sources. With more data from diverse sources like social media platforms, remote sensors, and detailed reports – data mining offers the tools to explore Big Data and turn it into actionable insights.

The data mining process can help to detect astonishing and intriguing relations and patterns in apparently unrelated piece of information.

To summarize this section, the major benefits of Data Mining are:

  • Helps create a searchable knowledge-base with reliable information;
  • Streamline your production and operations with better insights in your industry;
  • Avoid the use of costly and less precise statistical data applications;
  • Improve business decision making and inventory trend prediction;
  • Less costly technology that can be deployed on new as well as legacy systems;
  • Correct predictions and study of hidden patterns, trends and data;
  • Process massive business data in real-time without delays.

Data Mining Techniques

Data mining requires you to utilize a generic tool kit instead of following a pre-defined process. It is very productive process implied we select appropriate and accurate technique. However, the real challenge for the experts is to choose the most optimal techniques for specific scenarios considering the variety of options available for them.

Data Mining techniques that we have listed here are based on the data to be processed for finding trends, associations, intelligence, and business insights. Have a look at them:

  1. Association

Goal of association technique is to link two apparently unrelated activities or events. Association as a data mining technique helps businesses to craft their marketing plans in better way.

  1. Classification

As you can predict from its name, classification is a technique for analysis of data that first groups various data values as per their behavioral proximity with different classes. In the end, you will get classified data in multiple classes, while data in each class meeting a particular common criteria.

  1. Clustering

Clustering is a bit different from classification technique, as it does the grouping of data but not on the basis of pre-defined classes. In this technique, common features form the basis of grouping. Clusters comprise similar data sets organized in proximity to each other in one frame without having clear boundaries between them.

  1. Regression

Regression analysis predicts a value based on trends or patterns set by historic data. By doing this, it gives out the expected value of future events. The process is crafted to explore existing interaction between different variables. This process can calculate the possibility of a variable being derived from other existing variables. The goal of regression is to link between two distinct information pieces in one group.

  1. Prediction

Prediction method looks into the output of various other data mining processes, for example – trends, clusters, classes, sequential patterns, analytics data, etc. Thereafter, it combines these data sets and creates future event predictions as per timeline inclinations.

  1. Sequential Patterns

This technique requires a lot of transaction data with timestamps. After analysis, it groups similar patterns and create trends as per the recurring events.

Data mining tools

  1. MonkeyLearn – No-code text mining tools that utilize machine learning
  2. Apache Mahout – Ideal for complex and large-scale data mining
  3. Oracle Data Mining – Lets developers predictive data mining models for their applications
  4. RapidMiner – A data science platform for workflow visualization through data mining in Python.
  5. IBM SPSS Modeler – A predictive analytics solution to allow data scientists work with data assets and modern applications without much programming
  6. Weka – Open-source software for knowledge analysis through multiple data mining techniques
  7. Knime – This platform has pre-built analytics, integration and reporting components for your data mining projects.
  8. H2O – The open-source AI hybrid cloud for building models and applications using data mining in Python
  9. Orange – A powerful open-source data mining toolbox for analysis and visualization of data
  10. SAS Enterprise Miner – Solve business problems with data mining

Data mining Challenges

Large Dataset

In current times, data is being generated through multiple channels in any organization very rapidly – giving data mining processes a better chance to search through it. However, the same, i.e. Big Data is a bit problematic for existing systems considering its high volume, high speed of transactions of it, a number of data structures being used in it, and a lot of unstructured data.

Quality & availability of data

With enormous information or raw data there is incomplete, incorrect, ambiguous, fraudulent, and useless data. Data Mining tools and platforms can help to sort such data, but the users must provide full details about the source of the data. Also, it is your responsibility to check the credibility and reliability of input data sets to get precise results.

User Competency

While the purpose of data mining tools is to gain insights about the underlying data and give analysis reports, the task is not that easy. Modern tools now require design and user-friendly interface so that all kinds of users could use it. This way, we can reduce the efforts developers put during user training. Only the fully-aware users with a good understanding of business context, processes to be executed as per the use case, and data utility can make the best use of a data mining tool.

Data Mining Use Cases

DomainUse Case
ManufacturingUsing data mining manufacturers can track quality trends, overhaul data, production rates, and product performance data to identify production gaps. It helps to identify possible process upgrades that would improve quality, save time and cost, and improve product performance.
E-CommerceE-commerce websites use Data Mining to offer cross-sells and up-sells through their websites by using common buying patterns of their customers or using search patterns.
InsurancePrice prediction for their products, choosing new or existing customers to their pitch new offers, competitor analysis, etc. can be done using data mining tools.
EducationData mining techniques benefits instructors to view student data, predict accomplishment levels, analyze students’ performance, and discover students (or student groups) who need mentorship.
BankingBanks use data mining for understanding of market risks and meet the regulatory compliance obligations that change very often in this industry. Data mining techniques commonly applied to credit ratings and to intelligent anti-fraud systems to analyses transactions, card transactions, purchasing patterns and customer financial data.
RetailFrom the site location or new branch location suggestions. Data Mining can help retail stores, grocery stores and malls pick more profitable locations for their shops. Product selection, inventory trends, pitching of certain products to certain customers as per their purchase history, etc. can be handled through this technology.
Service ProvidersCustomer retaining as well as reasons of clients’ going away are studied and classified through data mining in the utilities sector where services are the major offerings of an organization. For example – Mobile operators look for the billing data, service related calls/interactions, grievance management for their tokens, quality of associated product, incentives offered and maintenance cost, in order to prevent and thereby reduce the rate of customers leaving.



As organizations continue to be flooded with massive amounts of internal and external data, they need the ability to extract that raw material down to actionable insights at the speed their business requires. Data Mining, being one of the fundamental techniques of modern business operation, helps to get the actionable insights and lend the needed help for your requirements. It is one of the pieces for the bigger picture that can be accomplished by working with larger data sets, Big Data or Smart Data.

Data Mining approaches are continually evolving and getting more efficient in digging out the insights from enormous amount of data from various sources. With Data Mining professionals at your service, knowledge discovery through this process and the further utilization of the precious knowledge becomes easy for your mission-critical needs. So, consider consulting the experts to make the most out of it.


Deploying Intelligent Supply Chain – Why is it Crucial and How it helps the businesses?

Delivering products, goods, and services to customers on time has become more important and complex than before. As the pandemic spread, organizations had to quickly adapt to the changes and build a supply chain that is efficient and will be able to meet the demand of customers.

In this fast-paced world, your organization needs to be quick and respond to the new changes and transform your business to be competitive, manage the cash flow, and be sustainable and flexible. The consumer and social demands have a lot of effect on the supply chain, thereby forcing organizations to create a unique and transparent supply chain that is swift and will be able to achieve consumer demands.

Also Read: Impact of Mobility Solutions on Logistic & Supply Chain Industry’s Dynamics

Earlier, companies were able to keep people waiting to sell their products and keep their business. But these are the days, as everyone is getting impatient and restless. If customers are not able to find a product at your store they quickly move to the competitor.

One of the best examples is, when the shipment of the iphoneX got delayed by 2 months, all the customers moved to buy Samsung galaxy9 and its variants. This shows how important the supply chain is for a business. Digitalization of sectors, such as production, transportation has become complex and all the activities in these sectors have to be done precisely and with utmost care. So here comes the need for an intelligent supply chain.

What is the need for an intelligent supply chain?

One of the surveys conducted in the year 2020 reports that the COVID impacted the personal and financial life of more than half of US consumers and this would last for additional 4 months. After this pandemic consumers have also become more mindful in making purchases by not wasting money and looking for different ways to save money.

The need for an intelligent supply chain is:

  • Improved supply chain efficiency

With the introduction of various new technologies like AI/ML and automation into the supply chain, there is a high chance of eliminating human error and also delays thereby improving productivity and efficiency.

  • Integrated Planning

An intelligent supply chain connects people, machines and all the assets of the industry. You can have up-to-date information and allow for better communication. Such an interconnected system will enable organizations to visualize the future ahead, take better decisions thereby allowing the growth of the organization.

  • Predictive maintenance and fault detection

Using technologies like ML, digital twin helps to visualize the data in real-time and also perform simulation on a virtual world to understand how the supply chain works and responds. Big data can be used to analyze and process the data to detect the faults in the machine and also estimate the remaining useful life of the machine.

Also Read: Utilizing the Power of Big Data Analytics for Oil and Gas Industry

  • Forecasting

As the entire organization is connected, it is easier to exchange information across various sectors of the organization and make wiser decisions using the insights that are obtained and also improve forecasting.

  • Improve efficiency and productivity

With the infusion of new technologies, the traditional supply chain can be transformed into a digital one which therefore increases productivity and efficiency.

Also Read: How can Big Data Boost the Revenue for Businesses?

How Intelligent Supply Chain Helps Businesses Respond to Fast-changing Consumer Needs?

  • Address customers’ changing needs

For any organization that fails to understand the changing customer needs, its competitors will and there is a high chance of losing valuable customers. Many companies believe in customer loyalty and expect them to come back again and again.

Companies must adapt to emerging technologies and adopt new practices to serve their customers. This means, opting for smarter solutions is needed for supply chain too. This will improve the quality of operation, while reducing human efforts in related procedures.

  • Keep an eye on Changing Market Trends

With intelligent supply chain at work in your business infrastructure, you can:

  1. Follow the footsteps of the customer to understand them. You should regularly keep a check on what your competitors are offering and lay out new strategies to attract more customers.
  2. Keep an eye on industry trends and upcoming technologies. Understand the market to launch new services and products.
  • Add new services and products

When you start understanding the new trends and study customer behavior it’s time to launch a new product or service. You have to find out new and exciting ways to serve your customer after launching the product. It is a waste of time and does not work out if you keep using the same old methods to serve your customers.

Also Read: KANBAN for Efficient Supply Chain Management – Advantages and Classification

It is advised to develop a new service model to improve productivity and efficiency. For example, take the example of law consulting firms, some bigger organizations require full-time consultation on all their legal proceedings and would be interested to pay on a monthly basis.

Some smaller organizations would require it for a few cases and would be willing to pay on a case to case basis. So, these consultancy firms need to understand the market and devise a normalized payment scheme for everyone.

  • To Speed up the current supply chain operations

A company would be able to respond and provide its customers quickly if its supply chain is fast, reliable, and should be able to serve a huge demand. Supply chains become one crucial part of all the business.

For example, consider the case of apple, during the 1990s, apple just had 2–3 three months of stock and another 2–3 months of finished goods. As a whole, they are just projecting 4 to 6 months’ demands, which was not a viable solution. So, they have later made changes in the entire supply chain and they were in a position to project demand of 1 -1.5 years.

  • Sales promotion

Many companies think that offering frequent discounts and sales will get them new leads and improve customer loyalty. This only clogs the inventory of the supplier and does not help in increasing sales. With intelligent supply chain solution, you can find out the ways to handle these promotions tactically, while actually making profits.

Other Suggestions to fasten up the Supply Chain

  • The most important component of speeding up the supply chain is to scrap off nonmoving goods and products. Most of the companies usually have their inventories filled with old stock which is a waste of place and unnecessarily clogs the entire system. This can be avoided by having a centralized connected system wherein you can analyze the stock and the fast-moving goods in the store. A proper analysis can help in forecasting the demand theory reducing the excess stock.
  • Simplify the point of sale system by rolling out mobile applications or web applications to take the order from the customers. As most of the people are now using the internet it is important to design a new system to take and manage the orders. Use industry-standard payment gateways, and also proper customer support to serve them with their queries.
  • Another important approach is to segregate the fast-moving goods, slow-moving and non-moving goods. It is advised to have separate supply chains catering to each one of them. The segregation can happen at the manufacturer or supplier end or inside the inventory.
  • With technologies like AI and ML, industries can easily manage the assets as they can get prior information about how the particular asset will function and the challenges they would be coming across. With this data, companies can reduce the cost of operation, ensure a neat and safe operation. These technologies can also predict failure beforehand.

Also Read: Advantages of Utilizing Data Science and ML in your Enterprise Operations

  • Using technologies like big data can allow retails industries to get insights about the demand and also understand the fast-moving goods. These predictions can help companies to estimate future demand and stock up their inventories to meet the customer’s demand. By doing this, industries will be in a position to reach the consumer demands and deliver the product quickly thereby reducing the lead times. Therefore companies will not incur any loss as they free up the inventory and can use this for other goods.
  • Use customer relationship management tools to manage the interactions between the company and the manufacturer. A lot of time gets wasted when there is a communication gap. A proper dashboard helps in tracking the products and goods that come from the supplies.
  • The most important component in the supply chain is to manage the fleet. Intelligent technologies like GPS can be used to track the position of the trucks and give a better understanding. Using fleet management software allows management to monitor large fleets, optimize routes and delivery time by analyzing the traffic and customer demand.


There is a long list of different methods to improve the supply chain and provide better services to the customers. But these are a few strategies that will help companies to improve their supply chains to adapt to the fast of moving consumer behavior. We tried listing them above.

Design your supply chain strategy that suits your firm’s objective that is resilient, and should be flexible to the changing needs. For this, you must hire Artificial Intelligence and Machine Learning experts with rich experience in supply chain automation.