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When I talk to data teams about the benefits of data observability and data quality, it’s often framed to prevent the negative impacts of insufficient data: poor decision-making, lost revenue, and even the erosion of customer trust.
With Gartner predicting that poor data quality costs organizations $12.9M per year, data observability becomes a no-brainer.
In the InsideView Alignment Report 2020, more than 70 percent of revenue leaders rank data management as the highest priority. Although many organizations have implemented a system for data collection and analysis, their biggest concern is now maintaining the integrity of their data.
The term "data integrity" is sometimes used as a process or a state of data. Either way, it refers to data being accurate, valid, and consistent across all data sources.
What is it like to work at Netflix as a developer? How do they think about culture, customers and engineering productivity?
In this incredible episode of Dev Interrupted, I bring in Kathryn Koehler, the Director of Productivity Engineering at Netflix, to chat about what makes Netflix so unique and why they are standardizing data-driven engineering today.
I had the opportunity to speak with Shawn Rogers, Senior Director of Analytic Strategy for TIBCO Software at TIBCO NOW 2019 in Chicago. During the event, Shawn was autographing copies of his new book Analytics: How to Win with Intelligence.
I began our discussion by asking Shawn:
In today's digital economy, it is generally understood that businesses must become data-driven enterprises to improve business performance, create sustainable value for consumers, build and run more innovative and efficient businesses to deliver unprecedented levels of performance to remain competitive.
According to the McKinsey Global Institute report, data-driven organizations are 23 times more likely to acquire customers, 6 times as likely to retain those customers, and 19 times more likely to gain in profitability.
A string of good decisions can easily propel a garage-born startup to greatness. But a few bad ones can bring even the most formidable organization to its knees. The key to minimizing costly decisions while maximizing profit-yielding ones is to make data the bedrock of your decision-making.
Top companies have been making data-driven decisions for a long time. Amazon, Box, Workday, Adobe, and other industry leaders have enjoyed huge success as a result of putting their faith in data over instinct.