Understanding SAP Conversational AI Bot (SAP CAI) Standard Implementation

SAP needs no introduction as this suite of ERP solutions has earned a magnificent reputation across the globe. Businesses of all shapes and sizes are lying their faith in this inventive resource. SAP CAI or SAP Conversational AI is another highly useful offering from SAP.

In this post, we’ll throw light on the utility of SAP CAI and the standard implementation style for this it.

SAP Conversational AI – An Overview

SAP CAI is an ingenious approach guiding enterprises and businesses through-and-through in designing creative and low-code chatbot platforms. Everything related to training, building, testing, and connecting the AI-driven chatbots is offered. Owning the power of SAP CAI, and strengthening the service delivery and user experience of a business is a doable task.

Read more: A Detailed Overview of How SAP Conversational AI Chatbot (SAP CAI) Works for Your Business

Here are some of the key traits of this platform.

  • The platform is low code allowing SAP solutions to get integrated with current operations quickly and seamlessly.

  • The world-class NLP technology support building of human-like robots that can analyze the inputs in a better manner.

  • The platform proffers intuitive UI and extensive bot builder assistance.

Standard SAP Conversational AI Implementation Style

The above text, if received due attention, must have clear the fact that the use of SAP CAI empowers an enterprise at various fronts. It’s time to learn about various plausible SAP CAI implementation styles. While one tries to make this step, pondering over a bit on the below-mentioned point is necessary.

  • What type of cloud structure you’re using?

  • Are you ready to deploy your bot on the cloud?

  • Do you have any plan to move to the cloud in the near future?

Once you have the answer to all these questions, you can move ahead and pick an implementation style. Presently, our focus is on the standard implementation style wherein the least possible development work is involved.

Download Guide: BOT Framework

Let’s carry forward by taking a generic example into context wherein the client needs:

  • An on-premise database deployed backend

  • To access the SAP Cloud platform for bot logic hosting

  • To relish over the perks offered by Bot Connector so that the bot can be integrated well with platforms like Skype, WebChat, and many more

The standard SAP CAI implementation process starts with entering the expression detail in any of the below-mentioned channels.

Once the expression is entered successfully into the bot connector, the tool converts it in a format that’s understandable by SAP CAI.

After this stage, the expression is moved to the dialog engine wherein the NLP engine separates entities and intents from the expression.

Up next, the dialog runtime comes into action to control the conversation flow as per the details of extracted entities and intents.

If there is a need for auxiliary backend system information for further movement then the dialog engine will call out bot logic for assistance. The desired information will be received in the JSON package. JSON package will feature conversation state, confidence scores, triggered skills, and other relevant information.

Bot logic will use this information, connect with the backend system seamlessly, and extract desired information to begin a transaction.

The next step is to expose the gathered information in an utterly secure ecosystem.

The data will be introduced to the storage system via SAP Gateway. Cloud Connector is used to allow OData services like SAP Gateway to be connected with the data storage without asking for the need for an opening port. This step is only required for an on-premise database. Bot logic will automatically connect to the data if it’s stored on the cloud and is exposed to web API.

Key Points to Know About Standard SAP Conversational AI Implementation Approach

  • End-to-end assistance of powerful tools like in-built Bot connector, Dialog runtime, and NLP Engine.
  • Understand that bot logic development will be your responsibility. However, it’s fairly easy.
  • In this approach, one has to configure SAP Gateway and SAP Cloud connector as well.
  • Data will be exposed to the cloud. Hence, one must enforce robust data security practices.
  • Enterprises are allowed to enforce user identity approaches like single sign-on into action.

Over to You Now

SAP CAI is a useful tool to improve customer assistance and service delivery. The standard implementation approach is useful when one needs to keep the resource requirement at the lowest level. However, the development of Bot connector, SAP Gateway, SAP Cloud Connector, and implementation of the SSO approach can be too daunting for a few. Stridely Solutions offers dependable assistance on this front.

Using the unmatched expertise over SAP CAI and standard implementation approach, it will take care of every relative development with full perfection. With their help, bringing SAP CAI to its full capacity is possible.

Stay Ahead of the Competition with SAP HANA Smart Data Integration: Here’s How

Businesses trying to be laced with updated technology to stay ahead in the competition have no dearth of options, as the market is flooded with such tools. Out of all the offered options that can address the existing operational challenges and empower a business at every front, SAP HANA Smart Data Integration folds a special place as it makes data processing easier than ever.

Effective data usage is what defines success for all sorts of businesses and SAP HANA Smart Data Integration opens a completely new world of opportunities. Let’s explore the utility of this vital tool and how it helps in successful weaving.

Existing Issues

Before SAP HANA Smart Data Integration came into being, customers were using multiple tools to execute ETL-based tasks. For flat file loading into HANA and batch processing, customers need to bring SAP Data Services into action.

Additionally, SAP HANA end-users seeking real-time data replications have to install SLT/SRS. If data duplication is not required at the targeted system then one must bring SDA into action to make most of the virtual tables.

Also read: Not alone data but analytics is transforming business

Seeing this, one has to get involved in the tedious and lengthy installation of three different tools just to create effective data utilization framework. This gave birth to the need of having a data integration tool that can handle everything related to data duplication or integration. Then SAP HANA Smart Data Integration happened.

What is SAP HANA Smart Data Integration (SDI)?

The parturition of the SAP HANA Smart Data Integration tool resolved many issues.

Before we delve deeper into its utility, let’s figure out what this invention technology means for end-users. This is high-end native technology, delivered as a part of the HANA database allowing use of all possible data integrations. Starting from data federation to end-to-end transformation of the data, it can handle everything smoothly.

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

It has been an active part of SAP HANA from the times and behaves like a bridge between the source and SAP HANA.


SAP HANA Platform

Image Source: SAP

The use of this technology leverages performance at every front via performing native SAP HANA implementation and execution. It needs a separate server for deployment, Data Provisioning Server, and is managed through-and-through by the SAP HANA Indexserver. The indexserver is a vital SAP HANA Smart Data Integration required for virtual table access and replication.

How SDI Works?

Having a deeper understanding of SDI modus operandi promotes the effective utilization of this tool and helps you enjoy better ROI. Let’s unfold this aspect as well.

Data provisioning Server (DPServer) and Data provisioning Agent (DPAgent) are two key functional components of SDI.

The Data Provisioning Server is commonly referred, as DPServer is the native server functional for the HANA database and can be accessed easily by activating the DPServer in the HANA configuration.

The second component, Data Provisioning Agent, is here to manage the entire HANA database-related SDI adapters and connections. It behaves like a communication bridge between adaptors and HANA. For effective functionality of SAP HANA SDI, it’s crucial to match the DP Agent version and HANA versions.

The use of different versions will not create a viable communication bridge. Adaptors taking care of the communication protocols are commonly deployed on the DP Agent only. The agent performs the below-mentioned tasks.

  • Gathering the data from the source
  • Compressing and sharing the collected data over HTTPS to HANA Cloud Platform. The shared data is backed with robust encryption.

Some of the DP Agents used are enabled in real-time while few are batch enabled. One another key aspect to understand is SAP HANA SDI Adapter Software Development Kit (SDK) which enables end-users to design need-based adapters.

Why to Consider SAP SDI?

Bringing SAP SDI into action reaps multiple benefits to end-users. The key ones are as quoted below.

  • Using SAP SDI makes execution of tasks like batch processing, virtual data access, and real-time replication.
  • Because of the full integration of SAP SDI with HANA UIs, its usage becomes easier than ever.
  • It’s very easy to configure and works wonderfully with every kind of source.
  • It can be deployed on cloud and on-premise with the same ease and perfection.
  • Performing real-time transformations is possible with SAP HANA SDI
  • End-users are endowed with the facility to make adjustments in the communication methods as per the data volume.
  • As data is pushed in real-time, it simplifies the process of delta loads and supports complex transformation.

The Right Kind of Assistance Is By Your Side

There is no second opinion that the use of SAP HANA Smart Data Integration allows an enterprise to make most of the HANA database. However, its effective implementation decides this.

Stridely Solutions have earned the unmatched competency and expertise in SAP HANA databases and SAP HANA Cloud Platform. We can guarantee for 100% satisfaction and customized implementation when you bring us on board.


A Comprehensive Guide to Statistical Analysis in SAP BW4HANA Infrastructure

SAP leaves no stone unturned to please its end-users and offers extended help. SAP BW4HANA is one such high-end offering. Technically, it’s an SAP HANA-powered packages data warehouse offered in both on-premises and cloud-based format.

The use of this data warehouse allows organizations to consolidate the entire database to gain deeper insights into it.

Also Read: SAP DWC: The Future of Data Warehousing

SAP BW4HANA implementation is not where an organization must stop and consider the SAP strategy complete. Regular statistical analysis of SAP BW4HANA infrastructure is crucial to assess runtime data, events, and key processes. In this blog, we’ll explore the importance of analyzing SAP BW4HANA and the need for statistical analysis.


Out of all the data warehousing solutions, SAP BW4HANA stands out as its only solution handling analysis with full perfection in the transactional and analytical processing ecosystem.

Additionally, it’s capable to reap the expanded benefits of SAP HANA in-memory RDBMS in full swing. It grants enterprises the ability to integrate live and historical data together leading to in-the-moment analysis and data-driven decision-making.

Also Read: Your Modern Data warehouse for Elevated Needs – Know about SAP BW/4HANA

SAP HANA gains an edge over traditional data warehousing solutions by endowing a more flexible and real-time approach. It supports smart data streaming in the case of IoT and smart data integration. The facility of pre-packaged EDW that one enjoys with SAP BW4HANA is absent in other data warehousing solutions.

Statistical Analysis of BW4HANA – When, When, and How 

Statistical analysis is the process of making sense of the collected data to find out the trends and patterns. It’s a subset of data analytics used to interpret research studies and determine the utility of software/tools.

In the case of SAP BW4HANA, statistical analysis is used to record the runtime data for SAP BW4HANA processes and events. The process involves calculating the total usage time by computing the accurate event runtime. The value of event runtime can be analyzed by subtracting the event start-time and event end-time. Additionally, statistical analysis is required to record the BW objects monitoring values from the Data Warehouse.

As BW4HANA is a type of data warehouse, the general data infrastructure statistical analysis process will be applicable. In general, the process is based on core data services technology or CDS. Based upon the areas, it makes the analytical queries accessible.

Also Read: SAP BW/4HANA – The Intelligent Enterprise Data Warehouse

CDS views analytical queries are used as default proposals for analysis featuring crucial information and are capable to execute in the BI client.

Additionally, one is allowed to define the Transient Providers-based queries, extracted from cube views. To make this possible, one must select the Search for TransientProvider field in the Query Wizard.

The use of CDS technology keeps the need for installation and activation of technical content away during the statistical analysis. Also, there is no need to load the data. Data is delivered in its real-time state.

Using the CDS technology, one can perform statistical analysis of data warehouse areas like data loading, process chains, data volume, and query runtime.

  • Data Loading Statistical Process  

To perform the statistical analysis process for data loading, one is allowed to use the RSPM request statistics and RSPM DTP load statistics.

RSPM Request Statistics involves using the RSPM request statistics with CDS view query “Rv_C_RspmRequestQuery” and cube view “Rv_C_RspmRequest”. RSPMREQUEST source table for the statistical analysis for data loading is also used.

Analytical Query 2CRVCREQQRY is the query used for returning the information request for a BW target object.

The next approach for statistical analysis of data loading is RSPM DTP Load Statistics which involves using query CDS view “Rv_C_RspmDtpLoadQuery” and cube view “Rv_C_RspmDtpLoad”. The reference source tables used for this approach are RSPMREQUEST, RSPMXREF, RSPMPROCESS, and RSBKDTP. The analytical query used in this approach is 2CRVCDTPLOADQ which returns the query information during the execution of the DTP.

  • Data Volume Statistics Process

Data volume statistical analysis is a tedious process and allows one to combine the statistics for the combined SAP HANA /cold store data volume, SAP HANA online data volume statistics, and cold store data volume statistics. The resulting analysis of combined data volume acts as an entry point for data volume analyses.

They provide a detailed analysis of the whole data volume at a particular time. For extra detailed information, one can gather the statistical analysis value of SAP HANA online data volume and cold Store data volume.

  • Process Chain Statistical Process

Process chain The statistical process can be started by combining the process chain status statistics and status and runtime information statistics.

To gather the statistics for the process chain status, one has to use process chain status statistics with query CDS view “Rv_C_PcmPcQuery” and cube view “Rv_C_PcmPcCube”. The analytical query used here is 2CRVCPCMPCQ and explains the present-date status of all the system-inherited process chains.

  • Query Runtime Statistical Process

One has to use query CDS view “Rv_C_OlapStatAQuery” and cube view “Rv_C_OlapStatACube” to execute the statistical analyses process for query runtime.

With the help of extracted statistical value, one can figure out how much time is required for the execution of particular user actions. The analytic query used in this case is 2CRVCOLAPSTATAQ and the source of the reference tables used are RSDDSTAT_OLAP (view), RSDDSTATHEADER, RSDDSTATINFO, and RSDDSATEVDATA.

  • Analytic Queries Authorization

A key part of statistical analysis is authorizing the analytic queries. It can be done using the S_RS_COMP object. Using this object, one can gain control over a user’s actions related to query processing. In case of prohibiting certain actions like query execution, one has to restrict the authorization value of S_RS_COMP as per the need of the hour.

  • Full Extraction 

Full extraction is the next stage of statistical analysis of the data warehouse and is performed using the full-extraction supportive code views. The CDS views are one of them and are flexible enough to be used seamlessly in operational data provisioning.

Using these cube views, one can easily craft a historical analysis model via snapshot loading and generating the time series.

To perform these two tasks, one has to access the ODP-Myself source system. In this system, taking the help of ODP context ABAP Core Data Services makes the creation of DataSource for operational data providers is possible.

Additionally, loading the snapshots into the DataStore object is possible. It allows the analytics performer possible to figure out whether or not a full view supports full extraction.

Statistics Views and Queries Time Details 

Prior to the launch of SAP BW/4HANA 2.0, the time details of views and queries were exclusively stated in the UTC format, with no utilization of local user time format. However, SAP BW/4HANA 2.0 now provides the time details for query CDS and cube views in the local time format, allowing users to access information in their preferred time zone.

Additionally, the CDS view query fields are offered in local user times. Previously UTC format-based fields are now available in local user times. This time difference can create havoc in the statistical analysis of SAP BW4HANA.

Hence, one must maintain consistency in the time details. To make this happen, make sure that Rv_C_RspmDtpLoadQuery (the load stat) and Rv_C_RspmRequestQuery (the requested stat) certain fields are delivered in both UTC as well as local time for the user.




Cloud ERP System for Modern Business Landscape

Innovation is one of the major elements of growth. An organization’s growth is dependent on how fast it can innovate and adopt new technology. Traditional enterprise resource planning systems were too rigid and failed to keep up with advanced business practices and technology. For this reason, Cloud ERP deployment has become one of the most preferred options for organizations of all sizes. Gartner has called it the ‘Everywhere Enterprise’ concept.

The value of ERP systems doesn’t reside in a single system but it expands continually. Cloud-based platform link accounting and finance automation with human resources, supply chain, tax technology, marketing, and sales, including several other applications.

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

Organizations with an efficient cloud ecosystem ensure quick and effective strategic adjustments, marketplace response, and disruption in supply chain management. They help in managing challenges of tax compliance in a better way in comparison to the counterparts that are less digitally advanced.

Factors that signal evaluation and replacement of legacy ERP systems

Obstacles in growth – ERP software features certain limitations which affect market expansion. Besides, they also block the organization’s way of achieving its objectives. It is true, especially in cases where expansion to new countries or regions involves complexities, tax compliance, accounting, and financial reporting.

Issues in data-sharing – Friction in system integration and data-sharing issues that help in impeding collaborations in different verticals of business are one of the major signs for updates in the ERP system. Legacy ERP and new applications integration can be time-consuming and cumbersome for maintaining, establishing, and updating. Extra maintenance and integration work may require an internal tax on business agility and innovation.

Deficiency in customer experience – Limitations within legacy ERP environments is also a major reason that hinders the ability of an organization to meet the changing expectations of customers, especially when it comes to customizations, mobile communications, and self-service portals that have tax compliance, pricing, and accounting implications.

Advantages of Cloud ERP Systems for Businesses

Upfront operating and infrastructure costs – It is one of the major advantages of cloud ERP solutions. The overall cost is reduced starting from implementation to the end process. On-premises ERP allows businesses to incur all kinds of upfront costs involving database creation, purchasing servers, consultants, initial implementation, security, backup, and IT staffing.

Organizations with ERP systems implemented on-premise need to bear additional costs to maintain on-call or in-house resources, updates, upgrades, and additional servers which increase with the growth of the company. The cloud ERP service provider manages and hosts the software on their own servers for avoiding upfront costs and other costs that are incurred for maintenance, IT staff, updates, and security. Continuous IT support is provided by the vendor which makes things easier for the businesses.

Also Read: Cloud & Innovation in the High-tech Industry: The Co-relation that you must think of

Speed implementation – Implementation time is a major hurdle faced by businesses that implement new ERP solutions. It affects the business downtime directly. Generally, a business may grow more quickly with the integration of a cloud ERP system into its existing business system. It doesn’t require any hardware setup or training or hiring IT staff.

Easy accessibility to business info – Businesses with cloud ERP systems can easily access all kinds of data and information instantly, from any device and anywhere. It helps in ensuring that the organization’s employees have access to the same data, irrespective of the business location or unit. It helps in ensuring easy and quick decision-making.

High-end scalability – With Cloud ERP solutions business scaling becomes easier as it eliminates the challenges of more number of servers as the users increase.  The growth of cloud ERP systems is aligned with business growth.

Companies may start with core and basic functionality and they move to advance methods as their business grows. The best part is that they don’t need to add hardware to enhance their systems.

With a cloud ERP solution, individuals can globally access information of businesses by connecting it to the web. Local servers aren’t important as the business grows by acquisition or merger. Users can bring new units online in real time. Generally, cloud vendors have data centers across the globe and they save customer data and other crucial info in different locations. It provides more reliable and better service.

Easy customization – Cloud ERP scales with a business and it can be tailored to fit the business requirements – right from the beginning as it evolves and grows. On-premise ERP software is customizable and it can be connected to the current system and software. It’s one of the major reasons that some organizations avoid upgrading their ERP on-premise systems and prefer running it on outdated technology.

Cloud ERP systems also integrate seamlessly with other products (cloud-based). Moreover, users can add new modules to the ERP system without additional hardware or downtime. It allows businesses to remain proactive and adjust quickly to changes and transformations that take place in the industry and in consumer trends. Plus, it also prepares the organizations for unforeseen circumstances.

No business disruptions and easy updates/upgrades – Generally, Cloud ERP vendors manage system updates and upgrades on a continuous basis. They align the services with advancing business needs to ensure customers use updated technology. Upgrading or updating ERP software needs more time. In some cases, vendors may need to hire contractors for managing the entire process. Updates with on-premise cloud ERP take only a few minutes and it generally occurs during “after-office hours” for preventing business disruptions.

Better compliance and security of business data – Rely on external vendors for housing the business data of a company safely. It is one of the major concerns for several organizations. Cloud ERP vendors facilitate users with better compliance and security. They provide affordable solutions to companies. Businesses may remain confident with proper data backup. The vendors are well-versed with the proper tools and planning required for disaster recovery.

Companies need to have business continuity and disaster recovery plan for their ERP on-premise solutions as they include catastrophic data loss risk in the case of a natural disaster, fire, break-in, or software or hardware failure.

Cloud ERP vendors offer end-to-end data encryption and top-notch security of data. However, it is to be noted that organizations are responsible for access management and identity of ERP users. Plus, it also secures their smartphones and other devices with internet accessibility.

Automation in the business process – In case of on-premise hardware failure the organization could spend a huge amount of their money and time transferring data and information to the storage system. Cloud ERP-based system works in coordination with the data centers and disperses the data redundantly. It is also advantageous in terms of giving access to crucial data and info over the internet.


Businesses with huge administrative and IT teams may have to deal with pushback from the company’s stakeholders. Administrators may move control over the automated process if they chose to move the ERP software from on-site to offsite. Also, with vendors like Stridely Solutions managing the entire infrastructure and maintenance the teams may also lose control over the operational process.

Organizations with strict policies for cyber security may face restrictions when hosting client info in the cloud. They may fail to experience the advantages of cloud ERP solutions or the ‘Everywhere Enterprise’ idea due to regulatory compliance problems. Hence, companies should make sure they tie up with vendors who accommodate their services with localized features and content so that users can easily comply with local regulations while managing other elements of global trade.