Short promotional explainer (video) describing challenges of blending transactional data during ERP migrations and multi-app analytics. It argues that traditional reporting tools cannot effectively blend historical transaction-level data (sales orders, POs, invoices), and promotes using a data warehouse (ETLplus/dataSelf) to combine legacy and live data for fast blended analytics (under 10 seconds).
Whether you're moving to a new ERP and want to blend data between your old and new systems, or just need to analyze data between two or more apps, blending data has its own set of challenges. Chief among those is the misconception that most of today's reporting technologies gives you the ability to combine old, new, and related data sets. Unfortunately, that's not the case. And and if we look at a typical data migration such as from one ERP solution to another, we can see what's missing. Historical transactions. This includes sales orders, purchase orders, invoices, and so on. Data elements used in transactional processing are seldom made available for blended analytics, and that's because these transactions contain too much data to be effectively blended and analyzed by traditional reporting technologies. This inability to blend transactional data has serious ramifications. Without access to transaction history, salespeople can't get a true picture of their clients habits, and management loses the ability to determine future strategies based on historical performance. But there is a solution. Transactional data sets can be combined if you use a data warehouse. A data warehouse blends the information from disparate data sets and performs blended analytics. Here's an example of blended analytics via a data self report that uses a data warehouse to report on both legacy and live sales data. Legacy data is on the left, the live sales data is on the right, and here's another data self report in which the data warehouse blends this information to make it appear as if it's all all coming from a single data set. An additional benefit of using a data warehouse is that this output is generated in under 10 seconds, blended, analyzed and delivered just when you need it. With ETLplus data warehousing, historical data loss is a thing of the past, and analyzing blended data from multiple data sources is no longer a thing of the future. With dataself, you can have your blended data and the insight that goes with it.
