AI technologies like ChatGPT are necessitating a fundamental overhaul of our educational systems and institutions. Getting the right answers to predetermined tests is no longer… Read More »Future of Education: Application not Regurgitation of Knowledge – Part II
Just a few days ago, January 28, we celebrated Data Protection Day, an international event aimed at promoting data privacy and security. In line with… Read More »Ensuring Data Security in Realtime Operating System (RTOS) Devices
The California Privacy Rights Act (CPRA) of 2020, also known as Proposition 24, was approved by California voters on November 3, 2020. Even though the… Read More »Why Should You Care About CPRA’s ‘Do Not Sell’?
As artificial intelligence (AI) becomes an increasingly important tool in health care, it offers unprecedented opportunities for improving patient outcomes, reducing costs, and impacting population… Read More »Training Data to Employ AI in Healthcare
The possibility to render historical data into comprehensive patterns has added soundness to many areas, and when we consider trading, it has left a giant… Read More »How to Explore Historical Data Patterns with Machine Learning
A recent HBR article, “Why Do Chief Data Officers Have Such Short Tenures?” by Thomas Davenport, Randy Bean, and Josh King, highlighted the Chief Data Officer’s (CDO) “Data-to-Business Innovation” challenge. The main charter for the CDO is to accelerate the Data-to-Business Innovation flywheel; to guide the business in becoming more effective at leveraging data and analytics to optimize its key business and operational use cases.
I received outstanding feedback from many folks in updating the Data Product Development canvas including Jon Cooke, Harsha Srivatsa, Craig (Doc) Savage, Melissa Perry, Raj… Read More »Data Subassemblies and Data Products Part 3 – Data Product Dev Canvas
A Business Discipline consists of systematic research, observation, measurement, and experimentation resulting in the assimilation of learnings into laws, theorems, concepts, principles, practices, frameworks, and formulas to enable the consistent application and ongoing enhancements from the real-world application of that discipline.
Trustable data can be defined as data that comes from specific and trusted sources and is used according to its intended use. It is delivered in the appropriate format and time frames for specific users.
With the world’s data multiplying in leaps and bounds, every organization is trying to make better business decisions in marketing, product development, and finance using insights from the data they hold. The value of businesses today can be measured by the quality of the data they hold.
