Data Democratization

I was recently on a Economic times panel discussion for Data Democratization and based on feedback , I realized this is a topic of interest and sharing just the introductory part of Data Democratization. 

15 years back, data used to be integral part of IT department and it used to be shared on demand with the selected people. Then came the tools like crystal report ( matured versions) and data access became easier for people. Soon several BI tools like IBM Cognos, BO, Oracle BI turned the data accessible to most of the senior management. In Last 10 years, BI and visualization tools got matured and there has been at least 20+ unique BI tools ( Refer last 5 years Gartner BI and Visualization Magic quadrant) like Tableau, Qlik, MS Power BI, Tibco Spotfire which got data accessible to the whole organization and this has enabled Data Democratization in true sense. Last 5 years has witnessed the advent of digital era and gig economy which has powered the data explosion - 20 Billion sensors, 6+ billion enterprise end points including mobility. Imagine a logistics company running 5000 trucks, if it gets data on every 3 mins from GPS, it has  20*60*24*5000 data point which was not there 8 years back. Add Fuel Sensor, Thermal sensor, Door Sensor, Driver monitoring data from camera and it will multiple by at least 8 times. There are lot of start- ups including leading e-com companies which runs on the data. Remember the most used phrase “Data is new Oil”. This has got the entire focus shifted to newer dimensions of Data Democratization like Versatility  of Insight and data security has become the integral implicit dimension. Previously Data Democratization just consisted of 3 main pillars – Trust , Usability and Speed of Insight

Trust on Data

Most of us have been either user or provider of the data in the enterprise world, how many times we had questions on credibility of the data itself ? - Several times ! Until as user trusts the data, it wont be used! So it is important to bring transparency with the users on data source, processing, periodicity of the data and quelling all doubts on data accuracy with conviction.

Usability

As time has passed by, there are several tools available including cloud based tools using data can be stored and accessed in much better way ( refer Datawarehouse and Data Lakes). There are several tools using which users can access authorized data sets. Easiest of them are BI & Visualization tools and most of them have self service features along with intuitive designs and this is the biggest agent of Data democratization among enterprises.

Speed of Insight

During my Consulting days 12 years back , We created some good data insights and visualization for a leading pharma MNC, due to data size initial dashboard used to take 17 mins to load. We did lot of technology interventions but couldn’t bring it down to less than 1.5 mins , still it got accepted by users and was used frequently. In Today’s world, more than 10-15 sec is not acceptable and technology maturity has made it possible in spite of having much more data than earlier.

Versatility of Insight

The fourth pillar which has been added recently is Versatility of Insight and major driver of this is millennial smart techno commercial population in the new digital era. Likes of Cloud providers AWS and Azure has made things much easier from technology perspective ( ETL, Warehouse, Insight, access layers, Visualizations, Data Layer API) and really brought agility to the whole data democratization. Each of these pillars and dimensions are whole subject in themselves.

All of us have our own data story either as user or provider and I hope you are able to reflect. If you have an interesting data story, why not to share as data democratization is here to stay and your stories will get less relevant with the every passing year!

#Data #Democratization #Insight #DataLake #Datawarehouse # Analytics #BigData #AI