How data is stored in databases is generally driven by the concepts of normalization – where you try to reduce data redundancy and improve data integrity. This has been the foundation of relational databases since their inception. However, when data is…
Over time, as more and more applications introduce more and more databases into your company, your data becomes siloed and getting accurate information becomes challenging.
The popular answer to this challenge has been the introduction of data warehousing…
When you’re looking for a definition of data democratization, you find a few common threads:
One of the most important steps in any machine learning project is the gathering, preparation, and cleaning of the data. Data is the backbone to your project and by spending the time and resources on this initial step you'll be better positioned for success…
What does your company’s approach to database management look like? You should always have an answer to that question.
Suppose that, at the end of a conference call, someone from the executive leadership team asks you and your boss to stay on for…
Everyone who analyzes data or tries to derive value from it, is affected by data preparation sooner or later.
Why?
Because organizations that identify, analyze and act on their data get the most out of it. That’s where quality of data becomes more important…
By next year, there will be more digital bits than stars in the universe, according to IDC. That’s a daunting prospect for any data professional. Add to that the complexity of data types and the ever-growing number of data sources, and it’s easy to see…
