Some of the world’s largest companies are making huge efficiency gains by adopting DataOps to eliminate data friction that is slowing innovation. DataOps is the alignment of people, process, and technology to enable the rapid, automated, and secure management of data. It improves individual and team outcomes by decreasing the distance between data sources and users and accelerating data flow.
In this five-part blog series, I will examine the process enhancements I have witnessed when companies adopt DataOps.
Eradicate Delays, Move Faster
Delays are crippling in many industries, even down to seconds. A great example is Formula 1 racing, where an “average” pit stop is around 3 seconds, and a great pit stop is under 2 seconds. When races are decided by mere hundredths of a second, a delay at the pit can be the difference between winning and losing. In the data-driven economy, even miniscule delays can incur heavy costs. TABB Group has estimated that a 5ms delay in a trading system costs a broker $20M.
While often not so dramatic, data delays are problematic in many businesses. Delays in getting timely information into an analytics or business intelligence (BI) system can increase the risk of faulty decision-making based on expired or incomplete information. Perhaps even more commonly, application projects that experience delays in getting the required data for development and testing (DevTest) often suffer from missed release dates, dropped features, or sacrificed testing cycles.
Automation and Self Service Boost Speed
The solution is to apply automation and self-service to delivery and operations and eliminate the data friction that causes delays. The decades-old approach of submitting tickets and then waiting for a bucket brigade to eventually make data available is no longer viable. Companies should be embracing technologies and policies that empower their data consumers to get the data they need when they need it, while eliminating manual interaction wherever possible.
These same focus areas benefit data operators by allowing them to codify their best practices and controls into an automated data delivery pipeline. This frees up data operators from the mundane, trivial, and costly tasks of escorting data from point A to point B, and allows them to focus their talents on important business challenges.
When DataOps is employed, companies can achieve Continuous Data Delivery and enable Data Democratization. The end result is that business analysts always have the fresh, or real-time data feeds required to support effective decision-making. Your application teams are no longer held hostage by data delivery delays, and your IT and InfoSec teams are no longer inundated with ad hoc/emergency data-related requests.
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