Episode Title: Why this is the last podcast on Data that you should listen to.

Episode Summary: What is the need for one more podcast on Data? How will the Data Transformers podcast be different from other podcasts? Who is the podcast meant for? Who is being interviewed? This episode goes into all the What, Who, Why, When, Where, and How of the podcast.  

Youtube link: https://youtu.be/z1fVM6YjFCM

Technology Trends  - Ramesh  (starting 1:22): (1) Intelligent Transformation with Artificial Intelligence as main front. (2) Focus on decisions driven by analytics (3) Drive towards a data literate organization 

Technology Trends - Peggy (starting 3:30): (1) Focus on data privacy (2) Need for a good data governance program (3) Democratization of technology in general and analytics in particular 

Challenges (starting 7:43): Organizations refusing to accept that automation is needed to deal with processing of large volumes of data. Industry now has tools to efficiently automate many processes such as data discovery, data classification etc. Regulators and auditors are forcing companies to adopt automated processes. There is no going back.

Pragmatic approach to solve business problems using technology (starting 12:37): Find a tangible business problem to solve in a department, introduce technology to solve there by learning the process and challenges of scaling it.

Skills upgrade for employees (starting 15:48): Organizations also need to take into consideration that employees feel the pressure to upgrade their skills and knowledge. If organization is not embracing new technologies, employees will be forced to look elsewhere. That is also another factor to embrace new technologies.

Concerns about adopting new technologies (starting 19:43): Some industries (ex: financial svcs) are hesitant to adopt cloud computing as they are concerned about exposing data especially as it relates to regulation and compliance. Similar situation in some high tech industries as well.

Data quality issues (starting 21:02): One of the most pressing and important items is the data quality. As data is the underpinning of any technology be it analytics or AIML, organizations need to focus on data quality. Unfortunately many don’t take it seriously.

Low hanging fruits for organizations (starting 24:44): Organizations need to find low hanging fruits to justify investments in data quality. Some low hanging fruits are process automation. The ROI is easily justifiable in process automation. Of course, regulation/compliance can also drive efforts to clean up data.

Where to start? Tops down or bottoms up? (Starting 27:52): Should data strategy be driven tops down or bottoms up? Tops down is a long drawn out process but much more enforceable with proper education and training. A bottoms up approach from a lighthouse project can also be effective in showing results quickly and using that to spread in the organization.

Data Transformers Podcast

Join Peggy and Ramesh as they explore the exciting world of Data Management, Data Analytics, Data Governance, Data Privacy, Data Security, Artificial Intelligence, Cloud Computing, Internet Of Things.