Analytics can be derived from predigested data

When we talk about big data it’s easy to assume that the petabytes of data are unusable in the form in which they land in the storage pool. In addition to consolidating the raw data and associating it with other accumulated data sets, it’s often the case that the data has already been processed by the application that collected the data in the first place. So it’s important to remember to look at the tools that originated the data and evaluate the analysis already done. This can provide a valuable starting place for business level analysis that may be more immediately useful to line of business staff.

Ben Tai, Founder and Chief Executive Officer of DrivenBI sees application output as valuable starting points for business analytics. Tai explains, “When talking about business analytics, one is reminded that the result is only as good as the data that the business professional used for analyzing. Therefore, identifying the right stage of data to analyze is a vital part of the process. When it comes to self-service BI for business professionals, starting from what we call “summary data” would be the way to go.

“Summary data refers to what’s already aggregated to a certain level per the analytical requirements such as operational reports, finance reports, and sales records, as opposed to unpolished raw data such as operational transaction data, system transaction logs, etc., which requires being translated into meaningful data in order to for a business user to create their own analysis. The translation is usually being carried out by IT implementing a data warehouse or doing programing. As a result, it makes the data preparation for creating business analytics very IT complex and dependent for business professionals. Summary data, on the other hand, is much more comprehensible to business professionals and hence allows them to easily merge multiple sets of data together, applying custom computations on top of it, and then further filtering, trimming, and/or aggregating to accomplish their own analytical objectives – without depending on IT.

“Summary data could come from various sources including internal systems such as ERP, financial system, and manually maintained spreadsheets, as well as external systems such as online CRM, 3rd party cloud services, and social media. Therefore, an easy-to-use data acquisition tool that is capable of acquiring summary data from multiple sources is more than useful, it is essential.
“By offering an easy-to-use UI for configuring data sources, mapping, transformation, and scheduling, the right tool would enable business professionals to prepare data with only the minimum amount of IT support. And once that logic is in place, an automated process can be scheduled to refresh the data as frequently as desired to keep analytics up-to-date to support just in time decision-making. Further, cloud-native BI platforms would have the natural advantage when integrating data with other 3rd party cloud services.

“Identifying the right stage of data to analyze and choosing the right data acquisition tool are the two most important aspects of data preparation for business analytics. By doing them appropriately and then bundling with a cloud-native self-service BI platform, business analytics would then become practically useful and much more accessible to business professionals to drive dynamic KPI management as to achieve just-in-time decision making in today’s continuously changing business environment.”