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SAP EIM portfolio updates aim at improving data quality

SAP Enterprise Information Management (SAP EIM) portfolio has been updated to improve data quality, big data support, ease-of-use and SAP HANA integration.

Good data leads to good business decisions, and it's fairly obvious what bad data leads to. This has always been...

true in business, but now more than ever it's imperative to have good data in business systems because of the demands of real-time processes.

SAP has just released updates to its venerable SAP Enterprise Information Management (SAP EIM) portfolio that address the needs of running real-time business processes.

Data quality is not just "nice to have," it's vital for today's digital businesses, according to Philip On, SAP vice president of product marketing. SAP EIM has been updated with functions that help organizations improve data quality, including connectivity to big data sources, data stewardship that enables discovery and resolution of data issues, data preparation rules that business users can define and use, and cloud microservices that can be embedded into applications.

"In a digital economy, the need for information excellence is not only aspirational it's foundational [to] the success of the digital enterprise," On said. "Informational excellence is the ability to ensure that all enterprise data is trusted, complete and relevant for analytical or operational use. All CIOs and chief data officers should prioritize data governance and data quality initiatives so that they can achieve the result of information excellence."

Real-time processes need quality data

On explained that in today's digital economy companies run live, meaning that they need data available for real-time processes and analytics.

"They need to respond to customer demands instantaneously and we have SAP HANA as the foundation to deliver this real-time performance," he said. "The challenge customers have is the explosion of data volumes, types and systems that are creating and storing information so customers are struggling to keep up."

The updated SAP EIM products:

  • SAP Data Services provides new enhancements that provide out-of-the-box connectivity for integrating and loading large and diverse data types, according to On. This includes a new patent pending data extraction capability for fast data transfer between Google BigQuery to any on-premises or cloud database, such as SAP HANA, SAP HANA Vora, and Hadoop. It also uses Apache Spark as the engine to extract data from Hive tables to connect to Amazon Redshift and Apache Cassandra.
  • SAP Information Steward provides new functions for users to discover and resolve data quality issues, including the ability to view and share data quality scorecards on any device without having to log into the system.
  • SAP Agile Data Preparation allows users to share, export and import rules between different worksheets and data domains. The rules are shared through a central managed repository and through the ability to import and export via flat files. This gives users better business efficiency for preparing their data through the improved collaboration and reuse of rules, On explained.
  • SAP HANA smart data integration and smart data quality is included natively in SAP HANA with new functions for faster real-time replication, bulk or batch data movement, data virtualization, and data quality though a common UI.
  • SAP Data Quality Management microservices are cloud services that offer specific functionality that enables customers to choose what they want in terms of data quality functionality. This can help users clean their address data and append geocode by implementing the microservices into any application, On said. The microservices are integrated with SAP technology like SAP S/4 HANA and SAP Business Suite, and customers can use them in any non-SAP application as well.

Focus on data quality spot on

The focus on data quality is on the mark, according to Stewart Bond, director of data integration software at IDC Canada.

"When you think about the digital business and some of the companies that have been successful at it, it's really about the data," Bond said. "It's about monetizing the data and what you do with the data that's part of their success, so it's critical that the data has integrity. This means data that's trusted -- it has high quality, you know where it came from, you can trust that the data's correct, and the data is available to the people who need access to it when they need access to it."

Data governance is one of the keys for companies to meet the demands of data integrity, Bond explained. SAP's updates to the SAP EIM portfolio,  such as the new functions for data stewardship, allows more visibility into information policies and the ability to include workflows, which make governance easier and more manageable for data stewards.

Data governance a business process, not a technology

However, Bond cautioned that improved functionality alone will not solve problems with data quality.

"Data governance itself is not a technology, it's more of a business process and a data process that needs to be followed and that's why there are resources like data stewards out there that help enable that process," he said. "SAP's improvements around information stewardship help that data steward do their job more effectively in having those capabilities available to them."

One challenge that SAP EIM faces is a crowded and diverse competitive landscape, which is difficult for customers to navigate because head-to-head comparisons are hard to make with so many different capabilities and functions from many vendors.

Nevertheless, Bond said that the SAP EIM portfolio gives companies much of what they need to improve data quality. 

"They certainly have the tools and technologies that can help organizations figure out whether they've got data quality problems -- and they do have data quality problems, because everyone has data quality problems," he said. "These can help them figure out what and where those are and get to some of the root causes of the data quality issues so they can start to plug those holes before they have to bail the boat."

Next Steps

Governing the data stored in different systems is a key to deploying Hadoop successfully.

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