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May 18, 2020
By Christopher Reeves
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When it comes to talking about the features and benefits of software, it’s easy to fall into the trap of talking about ‘speeds and feeds’. So we asked Chief Technology Officer, Chris Reeves, to look at things from a different angle. This blog sets out his top three features to look for in data management & analytics software – such as Sage’s SD&A or our own ZAP Data Hub – but from a business value perspective:
In addition to the strong governance story of having all your data and metadata captured in one place, another benefit to data warehouses – and the best data management & analytics software – is the ability to capture history. Becuase many ERP’s and most cloud sources don’t provide full change-history for business entities and values that you might be measuring.
This means for example, if an opportunity is captured as $60,000, later increases to $70,000, and then $80,000, your sales pipeline (for this single opportunity) would show as a flat $80,000. Warehouse history allows for reporting the pipeline growth trend by capturing the history of changes over time.
We introduced our History Step with ZAP Data Hub 8.1 and it’s been fascinating to see the different uses our customers find for it, but the key value is that the History Step enables additional reporting over time, all to the end of identifying trends relevant to your business. If you’re interested in more detail I have an ongoing blog series on the History Step that you can find here.
Often, many of the source systems for your warehouse are close matches, in that the tables and columns align closely. The most common scenarios are:
• A set of similar Excel or CSV files.
• A source system where different companies are captured in different databases.
From the outset, ZAP Data Hub has provided immense support for these scenarios by automatically merging matching tables. More than just saving time, our capabilities around Source Union significantly reduce maintenance costs. Imagine merging a set of more than 100 databases, taking 50 tables from each. Amazingly this was a real-world scenario. Even if your principal data source does not store companies in this way, keep an eye out for other places where Source Union might save you significant time.
Finally, Publication Rules are key to how I like to use our own internal BI. When we’re all back in our office, we have a single live dashboard on the kitchen wall. And in addition to this, we make use of Publication Rules to identify all the anomalies at a more granular level in near real-time.
Publication Rules allow for quicker response times and feedback loops. They also save time, in that I need only glance at my dashboard on the way for soup, and I can trust important exceptions are in my inbox. From inception, ZAP Data Hub has offered sophisticated rules for publication including event-, condition-, and schedule-based. If you’re not currently making use of Publication Rules, I’d urge you to consider doing so.
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