Data isn’t oil. We should create it, not just extract it.

In many cases, a data scientist’s world is bound by the data he or she sees is available. Data is something to be extracted, not created.
Yali Sasson argues that data creation should be an attractive alternative to data extraction. When a data scientist decides a certain feature is likely to be valuable for a model, they should explore how the company can go and create the data. They shouldn’t limit their search for features to those that can be delivered using existing data sources.
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Today’s Chief Data Officer is proactive and value-creating.
The chief data officer role is evolving. Ten years ago, only about 12% of companies even had a Chief Data Officer. Today, the majority of companies do.
Ten years ago, the CDO was responsible for reactive data management and data strategy. Today, the CDO is responsible for transforming their organizations' data culture and creating value.
Below are the four “levels” of data and analytics maturity that a successful CDO can bring their organizations through:
- Reactive
- Opportunistic
- Repeatable
- Optimized
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Craze or Trend? The Analytics Engineer

An analytics engineer is situated halfway between a data engineer and a data analyst in the lifecycle of data. The role has had a rise to prominence over the past few years.
The role of an analytics engineer really is part data engineer and part data analyst, and we think it’s here to stay. It allows one person to be both more involved in the upstream of the data pipeline than a data analyst would be and closer to business needs than a data engineer would be.
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How to develop a business-driven data strategy
Ben Mellearts argues that most organizations have well-defined business strategies, but not good data strategies.
Do you have a strategy on how to extract value from your data? This article defines what makes up a data strategy and takes you through the 5 steps to create one for your business.
image source: Ben Mellaerts
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