Price of Bad Data vs Rise of Good Data

Price of Bad Data vs Rise of Good Data

The Price of Bad Data

If the “Customer” data had old or incorrect address, you’d be sending goods ordered to wrong address leading to a dissatisfied Customer, additional shipment charges and administrative/logistic efforts. If “Customer” Master had duplicates, transactions with the Customer would be spread across those multiple duplicate Customer Master records. The whole picture about the Customer (all the transactions) cannot be viewed, as queries would bring only those transactions that happen to be tied to the Master Customer Record. Read loss of cross selling and up selling opportunities. As a Customer Support person, you cannot find the order the Customer is talking about over the phone.

If there were duplicate Item/Material records in the master table, inventory on one of the duplicates would be low, triggering an automatic replenishment, while there was enough stock on hand under a different master record. If Purchasing department ordered on one of the duplicates and Manufacturing department is searching another duplicate’s bin in the warehouse, the situation can lead to productivity loss and lot of shouting over the phone. The purpose of an ERP system can be broken by bad data.

All above confusions can arise in a single ERP system. But generally, organizations have multiple Enterprise Applications in use, with some processes in place to maintain sync of data across the systems. The confusions can grow multifold in this scenario.

The Rise of Good Data

Processes, Data and People run your business. To have good processes, you have a set of Computer Applications to run. You hired the best employees to run your business. Coming to Data, you need to make sure that it is of the highest quality and readily available to all data consumers.

Facilitation of efficient Master data governance with ChainSys

You need to control, monitor and facilitate data creation (Master Data Governance). This will lead to accurate master and transactional data. You should also maintain the quality of data throughout its life on an ongoing basis (Data Quality Management). Quality data is maintained in Operational Systems and as well Data Lakes/Warehouses. The former is called Operational MDM and the later is called Analytical MDM. ChainSys dataZen™ is the right toolset to perform many of the above activities. Unlike the MDM systems and Data Hubs provided by major ERP vendors, dataZen™ is not tied to any one ERP system and is very agile in terms of easily configuring the tool to add meaningful and necessary DQM functions, cross checks on short notice. All systems over time accumulate bad data, which needs periodic cleanup. dataZen™ facilitates pulling a batch of data at a time, subjecting it to established quality checks, getting correction inputs/okays from the right stakeholders and pushing it back into the system. dataZen™ makes MDM fun and easy to do.

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API Economy

API Economy

If Al Gore invented the Internet, then I invented the API Economy.

I came across the word API, way back in 1987, when I was creating reports using a BTOS micro machine from Burroughs (Later Unisys). I had to include a “Sorting Package”, into the long Pascal code which would fetch records, sort them with Sort functions (aka APIs) and print them onto a dot matrix printer. I’m glad that APIs have survived so many years of onslaught from competing acronyms. I’ve survived too. (Y2K was a short-lived acronym, but it made a lot of money for many many companies). API is still a popular ad word in Google and we pay a ton to get traffic from people wanting help with APIs

APIs are as critical to today’s world economy as the Suez Canal was to Britain’s trade in the 18th and 19th centuries. They are similar to the loading/unloading bays of distribution centers. In data terms, they are load/extract adapters.

Did you know that the ChainSys Smart Data Platform™ controls and marshals 9000 bays (API Adapters) situated in 200 distribution centers (Enterprise Applications)? Most trucks, semis, or lorries do not process the goods they carry. But the ChainSys Platform has massage equipment, which can transform the data while in transit, to the requirement and fancy of the receiving Application.

Many Customers abandon an old distribution center (ERP Application) and open a brand-new distribution center (Higher or Cloud version of a new ERP). Chain-Sys has been successful in helping Customers throw away unwanted things (data) in the old center, clean up the things and unload them to the new center. That is data migration. Setups migration can precede data migration.

When the bays are of standard size, standard-sized trucks can dock easily. In the software world, there are standards at the technical level. For example, web services allow programs to send or receive data from a distant repository. That is technical excellence. By the same token, we cannot pull out a “Customer Data Record” from an SAP ECC system and push it into an Oracle Cloud. There is no industry standard yet forcing vendors to import and export in a particular format (XML etc.). Wouldn’t it be nice if there are standard XML formats for invoices, sales orders, customer records, supplier records, and so forth? EDI is one such standard. The functional world is still playing catch up. ChainSys has painstakingly mapped the columns of many source systems’ records to target systems. That is a smart move. Pick the source and target and lo and behold, you find a pre-configured “Data Flow” object within the ChainSys Platform to readily transport your records.

ChainSys offers you in a platter harnessed APIs for SAP ECC, Oracle E-Business Suite, SAP S/4HANA, Oracle Cloud Applications, Microsoft Dynamics, Hadoop, Hive, Cloudera, Oracle DB, Redshift, Salesforce, Workday, JDEdwards, Peoplesoft, and your Custom Applications.

Now that you have APIs to play around with, try data cleansing, master data management (MDM), build data lakes, catalog your enterprise data, use the APIs as building blocks to create dazzling new Applications that integrate with existing ERP Systems, move to a newer version of your ERP, etc. What you can imagine, you can get them done. Call the people at Chainsys to show you how to do some of these stuffs.

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A Fortune 500 Pharma Company’s successful journey on Master Data Deduplication

A Fortune 500 Pharma Company’s successful journey on Master Data Deduplication

With being one of the data-dominated industries, the pharma industry comes across various data management challenges. The regulatory compliance standards, document submissions, changes in SOP processes, mass data inputs in both domains of vendor details and patient details leads to duplicates & incorrect data entries, and complexities in financial architecture in regards to receipts, bill payments, and other purchase information.

For the next pandemic years, having a single source of truth or consolidated Master Data for the whole pharmaceutical sector is becoming increasingly important

How ChainSys streamline a Pharma company’s Master Data?

ChainSys’ dataZen provides a single source of truth to materials, customers, suppliers, formula, receipt, bills of material, pricing, equipment, and real-time data at scale to accelerate research and development and also to improve their time-to-market.

dataZen’s Master Data Management principles

  • A Single Platform for Data Quality Management (DQM), Data Governance & Master Data Management (MDM)
  • A multi-domain strategy ensures that nothing is overlooked
  • Configurable and agile, with very little or no programming
  • Built-in Data Quality, Profiling, Deduplication, Consolidation, and more
  • Easy to build workflows for Data Governance

How dataZen stimulates and reduces complexity with health care data?

ChainSys’ dataZen solution offers a flexible and minimalist business workflow, qualitatively distinguished data, a centralized customer hub for simpler form submissions, and an automated business rules engine to eliminate manual procedures.
Learn how dataZen benefited a fortune 500 pharmaceutical firm!

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