A single source of the truth. A great mantra – but hard to
achieve as data types, volumes, and frequency continue to explode. A
company that embarks on a campaign to create one source for all its
reporting and analysis needs must traditionally undertake a massive
enterprise data warehouse project, relying heavily on "extraction" of
multiple layers of data from underlying ERP solutions. Business logic is
then applied to the data, cleaning it and enhancing its usefulness, in a
process referred to as ETL – extract, transform, and load.
The Promises and Perils of ETL
ETL works well in traditional environments where reporting solutions are outside the transaction system – those designed so reporting and analysis functions didn't impair or slow transactional systems. In such systems, users would simply extract the data and then use tools to report and analyze.
Many companies, however, use the ETL "cleansing" process to hide the sins of bad transactional system data. Such an after-the-fact approach creates multiple problems. Data that has been cleansed and changed can be difficult to reconcile with underlying sources. And when you pull together data from multiple sources, cleanse, and report it, it can look fine at a summarized level – but unsummarized, it is still full of outliers or anomalies... useful, but definitely not the same. In addition, ETL-based changes to data rely on predefined (often IT-driven) extraction configurations not visible to the report user. Because the quality of underlying transactional data is hidden, business processes remain less than optimized. Cleaning up such an environment requires costly data management projects.
Finding and Correcting Bad Data
Powerful computing tools can now work with transactional data directly in the data sources, making it possible to quickly spot bad data and trends. The SAP® HANATM platform, for example, is an in-memory computing appliance that runs analysis on big data directly from transactional systems. Its speed and power make it possible to analyze data where it resides, without exporting it.
Taking Action with SAP HANA
Using SAP HANA, employees can use information and analysis within the context of business processes – then take immediate corrective action. Users can continually monitor and refine a process in real time, identify backlogs and opportunities, and affect performance as it happens – for example, adjusting inventory levels on the fly or authorizing limited-time promotions for in-store customers.
Learn More
Business Analytics Services from SAP can help you right your data sins while crafting an overall information strategy. Our consultants can also speed analysis across your organization using in-memory computing advancements such as SAP HANA.
For more information on how Business Analytics Services from SAP can help unlock the value of your data and support better, faster, data-driven business decisions, visit us online.
ETL works well in traditional environments where reporting solutions are outside the transaction system – those designed so reporting and analysis functions didn't impair or slow transactional systems. In such systems, users would simply extract the data and then use tools to report and analyze.
Many companies, however, use the ETL "cleansing" process to hide the sins of bad transactional system data. Such an after-the-fact approach creates multiple problems. Data that has been cleansed and changed can be difficult to reconcile with underlying sources. And when you pull together data from multiple sources, cleanse, and report it, it can look fine at a summarized level – but unsummarized, it is still full of outliers or anomalies... useful, but definitely not the same. In addition, ETL-based changes to data rely on predefined (often IT-driven) extraction configurations not visible to the report user. Because the quality of underlying transactional data is hidden, business processes remain less than optimized. Cleaning up such an environment requires costly data management projects.
Powerful computing tools can now work with transactional data directly in the data sources, making it possible to quickly spot bad data and trends. The SAP® HANATM platform, for example, is an in-memory computing appliance that runs analysis on big data directly from transactional systems. Its speed and power make it possible to analyze data where it resides, without exporting it.
Using SAP HANA, employees can use information and analysis within the context of business processes – then take immediate corrective action. Users can continually monitor and refine a process in real time, identify backlogs and opportunities, and affect performance as it happens – for example, adjusting inventory levels on the fly or authorizing limited-time promotions for in-store customers.
Business Analytics Services from SAP can help you right your data sins while crafting an overall information strategy. Our consultants can also speed analysis across your organization using in-memory computing advancements such as SAP HANA.
For more information on how Business Analytics Services from SAP can help unlock the value of your data and support better, faster, data-driven business decisions, visit us online.
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