Five Rewards of a Well-Executed Intelligent DataOps Strategy
Updated: Nov 11, 2020
DataOps is the next generation of Data Management
“Manually building data pipelines is the bottleneck to scheduling and delivering data to users. Combining DataOps & DevOps creates an intelligent digital business automation process that delivers higher quality data pipelines - Leonardo Dias, Head of Professional Services, Bluemetrix.
In the digitised world of today, data is changing at the speed of light. DataOps is an innovative and collaborative platform that presents best practices to bridge the gap between those who collate data and those who analyse it. Under this model, both the development and operations teams can work together as a single unit during the entire life cycle of a product, while also keeping their tasks segregated. This ensures data integrity, streamlined processes, and allows each group to focus on their core competencies.
The Significance of Intelligent DataOps
Data is the main driving force behind a successful business. However, Data Operations come with many sets of challenges. In typical setups, 80% of data prep time is spent on creating a data pipeline along with manual activities circling data collection, securing the data, or providing data transformation and validation. This means only 20% of time is spent on running and managing the data pipeline. Secondly, the level of visibility for all teams involved in data science projects can be quite blurred, members often only see the bigger picture. Intelligent DataOps tackles these challenges head-on by delivering accurate processes, project details, and timely collaboration for all team members.
The importance of well-executed intelligent DataOps strategy is underpinned by five core benefits as outlined below:
Five Rewards of a Well-Executed and Intelligent DataOps
According to data scientists, the amount of data doubles every 12 months, thus driving a high need for automating data operations. Data scientists spend a significant portion of their time preparing, cleaning, and labeling data to make it production ready. If Data Operations is well-planned and efficiently designed, organisations can reap meaningful benefits. Here are some key advantages:
1. Data-driven Businesses
Companies that invest in Intelligent DataOps are data-driven and successful. With the advent of DataOps, the business world is seeing a rise in data-first organisations and according to the McKinsey Global Institute, these companies are 23 times more likely to gain customers, six times more likely to retain them and as an overall result, 19 times more likely to create a profit margin.
2. Agile Development
Automated DataOps empowers data scientists to use agile DevOps methodologies that enables rapid iteration to improve models. The publication of newer models can be conducted independently in production without interfering with the development environment. Traditional data management runs on a Waterfall methodology where projects are executed with lengthy and intricate schedules with only one single deliverable as the result.
3. Enhanced Data Quality
Due to the automation of analytics, code checks, and measured rollouts, Intelligent DataOps enhances data quality and elevates it to a new level. The minimisation of unplanned work, together with the automation of tasks, guarantees minimal human error transferred to servers thus avoiding downtime or any unplanned network outages.
4. Increased Efficiency
Task segregation, coupled with coordination, is a key benefit of DataOps. It provides a bigger picture of dataflow which allows each team to focus on their areas of expertise without overstepping the boundary of other teams. However, if problems do arise, all teams can coordinate effectively and solve problems more efficiently.
5. Faster Delivery to Market
In the digitised world of today, competition is steep and brand loyalty is diminishing fast. If a business cannot roll out features and functions quickly, they risk losing customers. Intelligent DataOps can significantly reduce the time to market business products from weeks to hours. Along with speeding up the delivery process, DataOps also provides the added benefit of agility that is a necessity in a rapidly changing market.
Operationalising Intelligent DataOps for Analytics
Intelligent DataOps provides a modern approach to creating and managing analytics. This approach reduces time consumption, minimizes unplanned work, improves data quality, and encourages a faster delivery to market. With the inefficiencies eliminated, different teams can work arm in arm to improve data quality by creating new models and analytics that stimulate business innovation and competition.
Bluemetrix provides an Automated Intelligent DataOps platform creating the ideal foundation to support data management. Bluemetrix automates ingestion, schema evolution, governance, security masking, validation, and transformation. Bluemetrix, through automation reduces DataOps processing time by up to 70%, rapidly delivering production-ready data to analytics and data science teams.