DevOps concepts are applied to data management for analytics in DataOps and have proven value in the data analytics world. In terms of downstream analytics and data science teams, DataOps promises speed, efficiency, quality, and productionization of data delivery.

DataOps is a rising big data analytic trend, and it continues to grow in importance. Data are becoming more complex, and organizations are looking for new ways to align their data with their processes and people. To be able to handle substantial data sources in their data warehouses or lake houses, there is a need for better tools and integrations demanded by the digital economy.

What is DataOps

DataOps is a principle that helps organizations combine access to information for the employees that consume data and those that provide them.

DataOps borrows many DevOps concepts, which integrate software development and IT operations to improve products through speed, quality, predictability, and scale. These same concepts are also applied to data analytics.

Companies willing to become customer-centric and data-driven begin to optimize their decisions using all their data and predictive insights. Their employees have access to all the data to enable them to make better and smarter decisions. These insights can be used for the optimization of marketing and e-commerce management such as personalization, omnichannel, loyalty, ROI management, and predictive marketing like the next best actions and offers.

Objectives of DataOps

DataOps is founded on the concepts of Agile Development, DevOps, and Lean Manufacturing following the DataOps Manifesto that Crystalloids has signed. With DataOps you decide which data and insights have the highest priority and should be developed first.

An increasingly complex data landscape and dataflows have put a great deal of stress on data teams. Project backlogs have increased, while analytics and business teams continue to wait for new data required for their analytics and often lack confidence in the data they do receive.

What makes a DataOps team unique is that demand and supply are on one side and that the team decides what has the highest priority and should be developed first. A DataOps team is not only responsible for developing new solutions but is also responsible for maintaining the operational environment. In other words, the team builds new solutions, uses these new solutions to get even better insights, and manages the solutions at the same time!

DataOps capabilities in data pipeline tools

Speed

• Code-free data pipeline definition
• Reuse
• Collaboration
• Self-service UX
• Easy productionizing

Output (all the speed capabilities, plus)

• Flexible delivery and consumption
• Scalable execution engines
• Performance optimization
• Scalable governance

Quality

• ML-assisted data quality functions
• Data quality analysis
• Data usability
• Data completeness
• End-to-end, granular data lineage

Governance

• Complete, granular catalog and metadata
• Enterprise-level security
• End-to-end, granular data lineage
• Detailed auditing

Reliability

• Automated operations
• Data retention and archiving
• End-to-end, granular data lineage
• Data pipeline monitoring
• Granular logging
• Change auditing
• Problem alerts
  
  

DataOps offers you

1. A multi-disciplinary, self-organizing team, responsible for the development, maintenance, and operations.
2. All relevant skills on one team, from data engineer to data scientist to business owner, breaking down the departmental silos.
3. New functionalities are in production fast with the scrum approach, along with automated testing and monitoring.
4. Cloud platform used for high performance and scalability, and lower costs.

Bringing it all together

A broad range of DataOps capabilities is available from Crystalloids.

We use the DataOps approach at several customers to help them realize an agile customer information architecture and create a central customer view.

We can provide your organization with an agile DataOps team to deliver the best results faster and with more flexibility. In that way, you do not have to waste time and energy on recruiting and training your data professionals. You immediately have our DataOps team at your disposal, so that you can focus on becoming more successful, together. Our DataOps team is a multidisciplinary, self-organizing team that covers the whole chain from data ingestion to delivering actionable insights to drive your commercial decisions.

Together we will help you to become a customer-centric, data-driven, predictive enterprise, getting the best results faster and with more flexibility.

ABOUT CRYSTALLOIDS

Crystalloids helps companies improve their customer experiences and build marketing technology. Founded in 2006 in the Netherlands, Crystalloids builds crystal-clear solutions that turn customer data into information and knowledge into wisdom. As a leading Google Cloud Partner, Crystalloids combines experience in software development, data science, and marketing, making them one of a kind IT company. Using the Agile approach Crystalloids ensures that use cases show immediate value to their clients and frees their time to focus on decision making and less on programming.