The issue: Executives are different from data scientists & analysts. Executives really cannot afford to wait for answers. Their time costs a lot of money. They have a business to run and they need their answers pretty much right now. But how can we trawl though a massive data lake and give the executive the answer they need?

The main problem: As we gather more data into lakes, we carry the Legacy of big data lakes with us. The ETL processes that run overnight are large heavyweight processes that crunch the big unstructured data. If we try to run reports on these huge beasts there is a good chance the request may not complete for a variety of technical or architectural reasons involving the hardware, software, or the database architecture. And you can easily find yourself waiting for a report that just never completes for one reason or another.

The novel approach: To prepare reports with our MPP BI analytical engine we “cook” data with a completely different approach. Following our recipe, we leave the overnight ETL processes as they are, and instead focus on breaking the data down into meaningful subsets that can be reported on more quickly. So we split transform and combine the data from various data sources into meaningful and manageable chunks of data that the systems can handle, and produce quick results. It’s not just enough to split the data into smaller pieces though. We have to be smart about how we do this and keep in mind what data the executives want to be able to query. Our operation we call MPP BI Data Boring; it bores into the data, bringing all the appropriate data together for the Executive user.

The most important part is the integration of MPP BI Data Boring with a high-speed database system such as ClickHouse or Dremio. This means MPP BI Data Boring extracts a detached part of data from any unstructured data source like a data lake, Kafka or any other and transfers it to a rapid database. What’s more, some heavy operations proceed right in the heart of ClickHouse, relieving the load on the data source.

The solution: Though there are two secret ingredients in the MPP BI “recipe”: the first one is a question of the right data marts, subsets of the data that can be processed quickly and efficiently. The second one is the collection of templates that feeds the data sources to the fast and efficient ClickHouse with MPP BI Data Boring.

In recent tests our approach has shown itself to be 4-5 times faster than any competition.  Why tolerate slow results when there’s a much better way. Try the MPP BI Data Boring solution.