<![CDATA[DVW Analytics - Blog]]>Sun, 15 Mar 2026 02:11:05 +0000Weebly<![CDATA[SAP Data Preparation for AI and Machine Learning]]>Sun, 08 Mar 2026 10:40:11 GMThttps://www.dvwanalytics.com/blog/sap-data-preparation-for-ai-and-machine-learning
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​Every AI model depends on the data it is built on. For enterprise AI projects, that data almost always includes data from SAP. And getting SAP data into a state that an AI workflow can use is rarely straightforward.

This post covers the data preparation problem specifically: what it involves, why SAP makes it harder than most other data sources, and how DVW Analytics products address it as part of a broader AI architecture.

​The data preparation problem in enterprise AI

​Before a machine learning model can be trained, the data it will be trained on needs to be found, extracted, joined, cleaned, standardised and transformed into the structure the model requires. This is data preparation, and in most enterprise AI projects it accounts for a significant proportion of total project effort.

For data that lives in SAP, the data preparation challenge is compounded by the nature of SAP itself. SAP data is highly structured around business processes and objects, spread across multiple modules and often distributed across multiple SAP systems. Extracting it requires SAP-specific knowledge and SAP-specific connectivity. Joining data across SAP modules, or between SAP and other enterprise systems, requires understanding of the SAP data model. Preparing it for AI workflows requires all of this to happen reliably, repeatably and on a schedule.

Organisations that approach this with manual processes (e.g. scheduled database queries, flat file exports, hand-maintained spreadsheets) find that the data preparation step becomes a bottleneck that limits how current their AI models can be and how frequently they can be updated.

​Where DVW Analytics fits

​DVW Analytics products are integration software. They connect SAP to analytics, automation and data platforms including Alteryx, KNIME, Dataiku, Power BI, Databricks and Snowflake using direct, native connectivity that does not require middleware, staging databases or ABAP development.

In an AI context, that connectivity is the starting point for data preparation. DVW handles the SAP extraction layer: pulling data from SAP Tables, SAP BW Queries, SAP HANA Views, SAP OData services, SAP T-Codes and more, and making it available inside the platform where data preparation and model development happens.

The platforms DVW connects to (e.g. Alteryx, KNIME, Dataiku and the DVW Flow Tool) all provide native data preparation capabilities: cleansing, transformation, feature engineering, joining across data sources, handling of nulls and outliers and more. DVW supplies the SAP data. The platform does the preparation work.

The result is a pipeline in which SAP data is extracted, prepared and delivered to the AI workflow as a scheduled, automated process rather than a manual one.

​A practical example: demand forecasting on SAP data

​Consider a demand forecasting model that needs SAP sales history, inventory levels and open purchase orders.

Without direct SAP connectivity, a data engineer manually exports data from SAP SD, MM and Purchasing on a weekly basis, processes it into a usable format and uploads it to the data science environment. The model runs on data that is already several days old by the time it is used.

With DVW, an Alteryx, KNIME or Dataiku workflow connects directly to SAP, extracts current sales, inventory and purchasing data, joins it across modules, applies cleansing and transformation steps, and delivers a prepared dataset to the model. The workflow runs on a schedule. The model always works on current data. The manual step is removed.

The same pattern applies to other AI use cases built on SAP data: predictive maintenance on SAP PM data, customer scoring on SAP CRM and SD data, financial anomaly detection on SAP FI data, workforce modelling on SAP SuccessFactors data.

Data from other sources alongside SAP

​SAP rarely tells the whole story on its own. Demand forecasting models benefit from external market data and weather data alongside SAP sales history. Customer models benefit from web behaviour data alongside SAP transaction data. Maintenance models benefit from sensor and IoT data alongside SAP PM records.

Platforms like Alteryx, KNIME, Dataiku and the DVW Flow Tool are designed for exactly this kind of multi-source data preparation. DVW supplies the SAP connectivity within those workflows. Other source connectors supply the rest. The preparation and integration of all sources happens in the same workflow, producing a single prepared dataset for the AI model.

This is the architecture DVW operates within: not a standalone tool, but the SAP data layer inside a broader data preparation and AI workflow.

​Writing AI outputs back to SAP

​Data preparation for AI is not always a one-way flow. Many AI use cases produce outputs that need to find their way back into SAP: forecast figures posted to SAP Integrated Business Planning, risk scores written to customer records in SAP CRM, quality flags updated in SAP Quality Management, anomaly alerts raised in SAP workflows.

DVW products support write-back to SAP using BAPIs, IDocs, OData services and other standard SAP write mechanisms. This means the full cycle (i.e. extract, prepare, model, write back) can be handled within a single workflow, without additional integration work.

​Getting started

​If your organisation is working on AI or machine learning projects that involve SAP data, DVW products are available as a free 30-day trial with full functionality.

If you use Alteryx, trial the DVW Alteryx Connector for SAP. If you use KNIME, trial the DVW KNIME Connector for SAP. If you use Dataiku, trial the DVW Dataiku Connector for SAP. 

The DVW Flow Tool reads and prepares SAP data and delivers it to Databricks, Snowflake and other platforms, supporting data engineering workflows that feed downstream AI and analytics systems.

Free Trial | Contact Us | DVW Alteryx Connector for SAP | DVW KNIME Connector for SAP | DVW Dataiku Connector for SAP | DVW Flow Tool
]]><![CDATA[SAP Data Made Easy for AI-Driven Insights: Unlock the Power with Alteryx AI Data Clearinghouse]]>Thu, 26 Feb 2026 14:49:57 GMThttps://www.dvwanalytics.com/blog/sap-data-made-easy-for-ai-driven-insights-unlock-the-power-with-alteryx-ai-data-clearinghouse
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Are you ready to turn your SAP data into actionable AI insights without the complexity?

Join us on Wednesday, 22 April 2026 at 3:00PM AEST / 6:00AM BST for this exclusive DVW Analytics webinar, in collaboration with Alteryx, and discover how to effortlessly integrate SAP data into your AI ecosystem — enabling smarter, faster decision-making.​
What’s in it for you?
  • Empower any user to harness SAP's rich data for impactful AI-driven insights - no advanced technical skills required. 
  • Ensure your datasets retain SAP’s critical business logic to improve accuracy and trust in your AI models. 
  • Accelerate your AI application development process, reducing time-to-value. 
  • Embed AI seamlessly into end-to-end SAP workflows for smarter business operations.

Whether you're looking to enhance your analytics capabilities or scale AI initiatives across your organization, this session will show you a new way to maximise your SAP data's value.

Don't miss this event. Register today!
​
​​Free Trial | Demos | Pricing
]]><![CDATA[SAP Data in Power BI for Any User: On-Demand Webinar]]>Wed, 25 Feb 2026 00:00:00 GMThttps://www.dvwanalytics.com/blog/sap-data-in-power-bi-for-any-user-on-demand-webinar
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If you're spending hours each week extracting SAP data into spreadsheets just to get it into Power BI, you're not alone. Most organisations rely on IT to build custom reports or pull data on request, which means long backlogs and slow turnaround. In the meantime, teams fall back on manual exports and Excel workarounds to keep things moving.
There's a better way.

In this on-demand webinar, we demonstrate how the DVW Flow Tool lets any business user connect to SAP data, prepare it, and visualise it directly in Power BI. No custom development, no coding, and no waiting on IT. Using the Flow Tool's low-code interface, you can go from SAP to a Power BI dashboard in minutes, right from your own laptop.
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You'll see a practical, hands-on walkthrough of how self-service SAP reporting works and how it can help your team eliminate bottlenecks and get to insights faster. 

Watch the recording here

​Want to try it for yourself? Sign up for a free trial of the DVW Flow Tool.
]]><![CDATA[SAP Financial Reporting, Audit & Control - Automated!]]>Thu, 19 Feb 2026 00:00:00 GMThttps://www.dvwanalytics.com/blog/sap-financial-reporting-audit-control-automated
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Professionals in SAP Finance and Audit functions often find themselves diving into large “haystacks” of data to uncover very small “needles.” With each passing year, those haystacks grow larger and the needles harder to find. At the same time, month-end reporting is facing increasing regulatory pressure, higher audit expectations, and growing complexity in SAP-based finance environments. Yet many legacy processes still rely on manual, time-consuming, and inconsistent validation procedures.
Join us on Wednesday, 18 March 2026 at 3:00PM CET / 10:00AM EST for this DVW Analytics x KNIME webinar and discover, through practical use cases, how to access detailed SAP finance data using well‑controlled, audit‑ready processes that help accelerate month‑end activities.

In this 45-minute session, you’ll learn how to:
  • Address common SAP finance reporting challenges
  • Move toward a more continuous and repeatable audit approach
  • Reduce manual effort and reporting risk
  • Operationalise controls through a deployable data application
Don't miss this event. Register today!

​​Free Trial | Demos | Pricing
]]><![CDATA[Automating Employee Master Data Migration for SAP SuccessFactors & SAP S/4HANA]]>Fri, 05 Dec 2025 00:00:00 GMThttps://www.dvwanalytics.com/blog/automating-employee-master-data-migration-for-sap-successfactors-sap-s4hana
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Moving to SAP SuccessFactors is a major step for any organisation. One of the earliest and most important challenges is preparing employee data so it can move cleanly from SAP S/4HANA into the new environment. Employee master data is connected to payroll, benefits, talent processes, and organisational reporting. Any issues in the data can create delays or trigger costly rework during a SuccessFactors implementation.
DVW Analytics offers an employee master data migration solution that removes complexity and gives project teams a structured, repeatable approach. The entire process is built using standard SAP application programming interfaces. There is no custom development and no heavy configuration. Instead, organisations follow a clear four stage workflow that extracts, validates, loads, and synchronises employee data across systems.
Also available on YouTube.

The Challenge: Complex Employee Data and the Need for Accuracy

Employee data is detailed and often inconsistent across systems. Addresses may be incomplete, old values may still exist in the master record, and the information stored in SAP may not match what is required for SuccessFactors. These challenges lead to:
  • Manual extraction and review
  • Large spreadsheets that are difficult to maintain
  • Slow and repetitive data cleansing
  • Limited visibility into which records are ready to migrate
  • Increased project risk

SuccessFactors implementations depend on clean data. Without a structured approach, teams may struggle to deliver a smooth transition.

The Solution: A Four Stage Process for Consistent Employee Data Migration

DVW Analytics removes uncertainty with a migration approach that is controlled, easy to understand, and based entirely on SAP standards. Each stage contributes to a predictable, high quality outcome

Stage One: Extracting Employee Master Data from SAP S/4HANA

The first stage extracts employee master data from SAP S/4HANA. This includes personal details, organisational information, and the correct address records for each employee. Because the extraction uses standard SAP application programming interfaces, it is reliable, repeatable, and accessible for both technical and HR project teams.

Stage Two: AI Supported Address Validation for Data Quality

Once extracted, the data is passed into the DVW AI supported address validator. This tool checks the quality of each address and identifies issues such as missing fields, inconsistent formatting, or incorrect country specific structures. Where possible, the validator proposes corrected values to reduce the amount of manual remediation required.
Any records that still need attention are exported for review. This step dramatically improves data quality before anything is loaded into SAP SuccessFactors.

Stage Three: Loading Clean Employee Data into SAP SuccessFactors

After validation, the clean data is loaded directly into SuccessFactors. This step once again relies only on SAP standard application programming interfaces. There is no custom code and no additional infrastructure. The process ensures that every employee record enters SuccessFactors in a consistent, ready to use format.

Stage Four: Writing SuccessFactors Employee IDs Back into SAP S4HANA

The final stage writes the newly issued SuccessFactors employee ID back into SAP S/4HANA. This ensures synchronisation of records between the two systems. Project teams can immediately identify which employees have migrated and which are still pending. This step is vital for audit purposes and helps maintain clarity in the overall migration timeline.

The Benefits: Reduced Risk and Accelerated Migration

The DVW Analytics approach delivers significant value for organisations preparing for a SuccessFactors transition. Key benefits include:
  • A clear four stage process that is easy to follow
  • Improved accuracy through AI supported data validation
  • Faster preparation with no custom development
  • Clean and consistent employee data
  • Greater visibility into migration progress
  • Stronger confidence in both SAP and SuccessFactors data integrity

​This structured method accelerates time to value and reduces the risk of issues during a SuccessFactors rollout.

Conclusion: A Smarter Path to SuccessFactors with DVW Analytics

Preparing employee master data for SAP SuccessFactors does not need to be complicated. With DVW Analytics, organisations can move through a clear and predictable process that prepares, validates, loads, and synchronises employee records across both SAP systems. This improves data quality, reduces manual effort, and gives implementation teams a reliable foundation.

Begin improving your SAP migration workflows today.Start your free trial of the DVW Flow Tool.
]]><![CDATA[Transforming SAP Migrations with Alteryx and DVW Analytics: Fast, Accurate, Repeatable Workflows]]>Thu, 20 Nov 2025 00:00:00 GMThttps://www.dvwanalytics.com/blog/transforming-sap-migrations-with-alteryx-and-dvw-analytics-fast-accurate-repeatable-workflows
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​SAP data migrations are some of the most complex activities an organisation can undertake. From multiple mock migrations to understanding every transformation applied to the data, teams need tools that deliver accuracy, transparency, and repeatability at scale. When SAP landscapes change, whether through upgrades, moves to SAP S/4HANA, or restructuring, migration teams require a solution that integrates seamlessly, supports automation, and lets both IT and business users collaborate through clear, visual workflows.
​This is exactly where Alteryx and the DVW Alteryx Connector for SAP work together to transform the migration process.
​Also available on YouTube.

​The Challenge: Complex SAP Migrations Require Repeatability and Clarity

SAP migrations involve numerous moving parts:
  • ​Multiple mock runs with validated, consistent results
  • Transformations that are easy to understand and replicate
  • Automated processes that eliminate manual error
  • Clear reconciliation of differences between systems

​Traditional methods often rely on manually comparing spreadsheets, writing custom code, or stitching together tools not built for SAP integration - all of which introduces risk.

SAP teams need a way to simplify extraction, transformation, validation, and reconciliation, without sacrificing the depth and control required for enterprise systems.

The Solution: Accelerating Migration Projects with Alteryx and DVW Analytics

​Alteryx has long been recognised for its flexibility and ability to build repeatable workflows. When combined with the DVW Alteryx Connector for SAP, teams gain the ability to read from and write back to almost any SAP object and perform migrations far more efficiently.

What DVW Adds to Alteryx

  • Instant SAP integration: Connect to SAP systems in minutes not weeks.
  • Universal object access: Extract tables, transactions, documents, and more.
  • Write-back support: Push data into SAP using BAPIs, IDocs, OData, or RPA.
  • Visual workflows: Make transformations transparent and easy for both IT and business stakeholders.

​This combination gives teams a fully governed, fully auditable workflow engine tailored for SAP migration success.

Walkthrough: Using DVW Tools to Reconcile SAP ECC and SAP S/4HANA

One of the biggest challenges in any SAP migration is reconciliation—confirming that values match between the source and target systems.
Using the DVW Reconciliation tool within Alteryx, teams can:
​
  1. Connect to both SAP ECC and SAP S/4HANA simultaneously
  2. Extract table content in parallel
  3. Compare differences instantly—no complex joins or filters required

The tool highlights:
  • Records only in the source system
  • Records only in the target system
  • Records with field-level differences

In the example shown in the demo recording, 228 records existed only in the source system, 53 existed only in the target, and the join anchor displayed field-level mismatches such as decimal inconsistencies for units of measure.
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This gives teams immediate insight into configuration issues that could block migration readiness.

Automated Reporting and KPI Tracking

With built-in Alteryx reporting tools, teams can automatically email validation summaries to data owners thus ensuring issues are assigned, tracked, and resolved quickly.
​
Beyond reconciliation, DVW and Alteryx enable KPI tracking within the same workflow, including:
  • Record counts
  • Transformation quality
  • Runtime benchmarks
  • Volume changes
  • Progress against migration milestones

​These insights help project teams identify early blockers and maintain confidence in migration readiness.

The Benefits: Faster, Clearer, More Reliable SAP Migrations

Using the DVW Alteryx Connector for SAP gives organisations the power to:
  • Accelerate data migration timelines
  • Improve transparency across all transformation steps
  • Automate key tasks and reduce manual rework
  • Strengthen auditability and compliance
  • Bring IT and business teams together through visual workflows
  • Deliver consistent migration outcomes across every mock run

​This is SAP integration made simple, robust, and scalable.

Conclusion: Modernise Your SAP Migration Process

Fast, accurate, repeatable migrations are possible when your workflows integrate seamlessly with SAP and support automation at every stage. Alteryx, combined with DVW Analytics, gives your teams the visibility, repeatability, and control they need to deliver flawless SAP migration projects.

Start transforming your SAP migration workflows today. Begin your free trial of the DVW Alteryx Connector for SAP.
]]><![CDATA[The most important SAP Inventory Management tables for users of  Alteryx, KNIME, Dataiku, Microsoft, Databricks, Snowflake & more]]>Thu, 30 Oct 2025 00:00:00 GMThttps://www.dvwanalytics.com/blog/the-most-important-sap-inventory-management-tables-for-alteryx-users
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​In this blog we identify the most important SAP Inventory Management tables for users of:
SAP Inventory Management tables are found in the following SAP systems:
  • SAP ECC 
  • SAP ERP
  • SAP S/4HANA

SAP Inventory Management Transaction Tables

SAP Material Document Tables

  • MKPF - Header: Material Document
  • MSEG - Document Segment: Material

SAP Material Valuation Tables

  • MBEW - Material Valuation
  • ​MBEWH - Material Valuation: History

SAP Physical Inventory Document Tables

  • IKPF - Header: Physical Inventory Document
  • ​ISEG - Physical Inventory Document Items

SAP Inventory Management Master Data Tables

  • MARA - General Material Data
  • MAKT - Material Descriptions
  • MARD - Storage Location Data for Material

SAP Inventory Management Configuration Tables

  • T001K - Valuation area
  • T023 and T023T - Material Groups and Material Group Descriptions
  • T134 and T134T - Material Types and Material Type Descriptions
  • T156 and T156T - Movement Type and Movement Type Text
  • T188 and T188T - Conditions: Groups for Customer Classifications and Conditions: Groups for Customer Classes: Texts

Other Sources of SAP Table Information

Google is your best friend when searching for SAP Table data. Give it a go!

Next Steps

Register for a 30-day trial of our products.
​
Free Trial | Pricing | Contact Us
]]><![CDATA[The most important SAP Finance and Controlling (FI/CO) tables for users of  Alteryx, KNIME, Dataiku, Microsoft, Databricks, Snowflake & more]]>Wed, 15 Oct 2025 23:00:00 GMThttps://www.dvwanalytics.com/blog/the-most-important-sap-finance-and-controlling-tables-for-alteryx-users
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​In this blog we identify the most important SAP Finance and Controlling (FI/CO) tables for users of:
SAP Finance and Controlling tables are found in the following SAP systems:
  • SAP ECC 
  • SAP ERP
  • SAP S/4HANA

The "Big Two" SAP Financial Accounting (FI) Transaction Data Tables

  • BKPF - Accounting Document Header
  • BSEG - ​Accounting Document Segment
Table BKPF holds the Header data for all Financial transactions in SAP while table BSEG holds the Segment or Item data for all Financial transaction in SAP.  ​In Alteryx you will typically extract data from both tables in order to get the full picture for a Financial transaction.
There are a number of other SAP Financial Accounting transaction tables that can be used in association with BKPF and BSEG. 

The following tables can be used with BKPF:
  • BVOR - Intercompany posting procedures
  • BSIP - Index for Vendor Validation of Double Documents (Note: "Double" means Duplicate)

The following tables can be used with BSEG:
  • BSID - Accounting: Secondary Index for Customers (Open Items) 
  • BSAD - Accounting: Secondary Index for Customers (Cleared Items) 
  • BSIK - Accounting: Secondary Index for Vendors (Open Items)
  • BSAK - Accounting: Secondary Index for Vendors (Cleared Items)
  • ​BSIS - Accounting: Secondary Index for G/L accounts (Open Items)
  • BSAS - Accounting: Secondary Index for G/L Accounts (Cleared Items) 
In addition to the above the following SAP Financial Accounting transaction tables are useful to know:
  • BSEC - One-Time Account Data Document Segment
  • ​BSET - Tax Data Document Segment

Tables BSEC and BSET can be used in association with table BKPF.

Key SAP Controlling (CO) Transaction Data Tables

Cost Centre Accounting

  • COBK - CO Object: Document Header
  • COEP - CO Object: Line Items (by Period)
  • COSP - CO Object: Cost Totals for External Postings

Profit Centre Accounting

  • GLPCC - EC-PCA: Transaction Attributes
  • GLPCO - EC-PCA: Object Table for Account Assignment Elements
  • GLPCA - EC-PCA: Actual Line Items
  • GLPCT - ​EC-PCA: Totals Table

Important SAP Finance and Controlling (FI/CO) Master Data Tables

General Ledger 

  • SKA1 - G/L Account Master (Chart of Accounts)
  • SKAT - G/L Account Master Record (Chart of Accounts: Description)
  • SKB1 - G/L account master (Company Code)

Cost Centre

  • CSKS - Cost Center Master Record
  • CSKT - Cost Center Texts

Cost Element

  • CSKA - ​Cost Elements (Data Dependent on Chart of Accounts)
  • CSKU - Cost Element Texts
  • CSKB - Cost Elements (Data Dependent on Controlling Area)

Profit Centre

  • CEPC - Profit Center Master Data Table
  • CEPCT - Profit Center Master Data​

Accounts Payable - Vendor Master Data

Vendor Master - General Data

  • LFA1 - Vendor / Supplier Master (General Section)
  • ​LFBK - Vendor / Supplier Master (Bank Details)

Vendor Master - Purchasing Data

  • LFM1 - Vendor Master Record purchasing organization data
  • ​LFM2 - Vendor Master Record: Purchasing Data

Vendor Master - Company Code Data

  • LFB1 - Vendor Master (Company Code)
  • LFB5 - Vendor master (dunning data)

Accounts Receivable - Customer Master Data

Customer Master - General Data

  • KNA1 - ​General Data in Customer Master

Customer Master - Sales Area Data

  • KNVP - Customer Master Partner Functions
  • KNVV - Customer Master Sales Data

Customer Master - Company Code Data

  • KNB1 - Customer Master (Company Code)
  • ​KNB5 - Customer master (dunning data)

Useful SAP Finance and Controlling (FI/CO) Configuration Data Tables

  • M_KOSTS - Generated View for Matchcode ID KOST-S (Cost Centre Texts)
  • T001 - Company Codes
  • T001K - Valuation area
  • T077S - G/L account groups
  • TBSL and TBSLT - Posting Key and Posting Key Names

SAP S/4HANA Finance Tables

  • ACDOCA - Universal Journal Entry Line Items
With SAP S/4HANA, table ACDOCA contains all the Item data for Finance (Controlling (CO) and Asset Accounting (AA).
ACDOCA can be used as an alternative to:
  • BSEG - Accounting Document Segment
  • COEP - CO Object: Line Items (by Period)
Table BKPF still holds the Header data for all Financial transactions in SAP S/4HANA.

Other Sources of SAP Table Information

Google is your best friend when searching for SAP Table data. Give it a go!

Next Steps

Register for a 30-day trial of our products.
​
Free Trial | Pricing | Contact Us
]]><![CDATA[The most important SAP Purchasing (MM-PUR) tables for users of  Alteryx, KNIME, Dataiku, Microsoft, Databricks, Snowflake & more]]>Wed, 08 Oct 2025 23:00:00 GMThttps://www.dvwanalytics.com/blog/the-most-important-sap-purchasing-tables-for-alteryx-users
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​In this blog we identify the most important SAP Purchasing (MM-PUR) tables for users of:
SAP Purchasing (MM-PUR) tables are found in the following SAP systems:
  • SAP ECC 
  • SAP ERP
  • SAP S/4HANA

SAP Purchasing (MM-PUR) Transaction Tables

SAP Purchasing Requisition Tables

  • EBAN - Purchase Requisition
  • EBKN - Purchase Requisition Account Assignment

SAP Purchase Order Tables

  • EKKO - Purchasing Document Header
  • EKPO - Purchasing Document Item
  • EKBE - History per Purchasing Document
  • EKKN - Account Assignment in Purchasing Document

SAP Goods Receipt Tables

  • MKPF - Header: Material Document
  • ​MSEG - Document Segment: Material

SAP Invoice Receipt Tables

  • RBKP - Document Header: Invoice Receipt
  • RSEG - Document Item: Incoming Invoice

SAP Purchasing Master Data Tables

  • LFA1 - Vendor / Supplier Master (General Section)
  • LFB1 - Vendor Master (Company Code)
  • LFBK - Vendor Master (Bank Details)

SAP Purchasing Configuration Data Tables

  • T169G - Tolerance Limits, Invoice Verification
  • TIBAN - IBAN

Other Sources of SAP Table Information

Google is your best friend when searching for SAP Table data. Give it a go!

​Next Steps

Register for a 30-day trial of our products.
​
Free Trial | Pricing | Contact Us
]]><![CDATA[Working with SAP Data in Excel Made Easy with the DVW Flow Tool]]>Wed, 08 Oct 2025 23:00:00 GMThttps://www.dvwanalytics.com/blog/working-with-sap-data-in-excel-made-easy-with-the-dvw-flow-tool
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​Many organisations rely on SAP for financial reporting, operational processes, and transaction management. Although SAP is a powerful system, exporting data for everyday analysis in Excel is not always simple. Reports may require additional formatting, transaction codes can be difficult for new users, and manual exports often lead to inconsistency and delay.
​The DVW Flow Tool removes these barriers. It provides an intuitive drag and drop environment that brings SAP data directly into Excel in a clean, ready to use format. This enables finance teams, analysts, and business users to work more efficiently with the information they need without relying on repetitive manual steps.
​Also available on YouTube.

The Challenge: SAP Data Is Valuable but Not Always Easy to Use in Excel

SAP transaction codes and reports contain a wealth of business information, but exporting that data in a usable Excel format can require multiple steps. Users often face issues such as:
  • Subtotals that need to be removed
  • Missing header rows
  • Inconsistent column formatting
  • Repetitive manual downloads
  • Files that need rework before analysis can even begin

These barriers reduce productivity and increase the risk of errors.

​Organisations need a faster, more consistent way to extract SAP data into Excel.

The Solution: Fast and Simple SAP to Excel Workflows with DVW Analytics

​The DVW Flow Tool offers a clean, visual interface that simplifies every step of the process. Users build a flow by dragging blocks onto the canvas, selecting the SAP transaction code they want to extract, and choosing an output destination in Excel. The workflow becomes reusable and can be automated, so the data arrives exactly how the business needs it every time.

Creating a Flow to Extract SAP Data

The process begins by creating a new flow using simple drag and drop blocks. There is no need for technical configuration and no code is required. The user selects the SAP transaction code they want to run. In the example shown in the demo recording, the G/L account line item transaction is used.

​Once selected, the familiar filters and parameters from SAP appear inside the Flow Tool. This allows the user to choose an existing variant or define new parameters. The data can then be previewed to confirm structure and content.

Intelligent Formatting for Better Excel Outputs

The Flow Tool adds intelligent formatting that improves the output before it even reaches Excel. The tool automatically:
  • Adds clear header rows
  • Removes subtotals
  • Presents the data in a consistent way

​This means that the file requires minimal or no adjustment once opened in Excel. Analysts can begin working with the data immediately, improving efficiency and reducing manual effort.

Setting up the Excel Output

After previewing the data, the user adds an output block and specifies the Excel file and worksheet name. The tool provides flexibility to:
  • Create new files
  • Write sequential files
  • Append to existing files or existing sheets

​This allows a single flow to support daily, weekly, or monthly reporting without extra steps.

Running or Scheduling the Flow

Once the flow is ready, it can be executed immediately or scheduled to run automatically. This gives users complete control over when and how SAP data is refreshed. The information is sent directly from SAP into Excel in seconds.

​With this approach, organisations eliminate manual extraction, reduce repetitive tasks, and ensure consistent output every time.

The Benefits: Faster Reporting, Better Accuracy, Less Manual Work

Using the DVW Flow Tool for SAP to Excel processes provides several clear advantages:
  • Faster access to SAP data in Excel
  • A simple and intuitive interface for all user levels
  • Consistent formatting with automatic header creation and subtotal removal
  • Reusable workflows that save time
  • Scheduled runs that refresh data without manual effort
  • Reduced risk of human error
  • Seamless SAP integration supported by DVW Analytics

​This gives business teams more confidence in their data and more time to focus on analysis rather than extraction.

Conclusion: Bring SAP Data into Excel with Ease Using DVW Analytics

SAP data delivers valuable insights, but extracting and preparing it for analysis can be slow and complex. The DVW Flow Tool solves this challenge by offering a clear and efficient method to pull SAP data directly into Excel with accurate formatting and minimal manual work.

To experience the Flow Tool for yourself, visit the DVW Analytics website today and begin your free trial of the DVW Flow Tool.
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