Discover the DataOps methodology into a data-driven organisation.
Learn how DevOps and Data work together to benefit your business
DataOps is still a relatively new concept that has the potential to revolutionise the way organisations run their operations. The idea behind the data operations methodology is to have DevOps teams work together with Data Engineers and Data Scientists to create all the DataOps tools and processes necessary to transform your business
The DataOps approach, much like DevOps, is based on the tenets of the agile methodology. Hence, adopting DataOps in your projects will ensure that you get access to analytic insights that meet your individual business needs on a continuous basis.
Another similarity between DevOps and DataOps implementation is the end-to-end nature of delivery—DataOps teams are responsible for the entire project lifecycle: data, tools, code, and environments.
Download our latest complimentary eBook to learn how you could apply the DataOps methodology in your business to see greater value gains, streamline your operations, and reduce costs.
DataOps Guide Overview
What’s inside the eBook?
Part 1. Delivering Business Intelligence Iteratively—Fact or Myth?
Agile business intelligence is possible. Applying agile principles when developing data analytics solutions means that the primary focus of your data projects will be to bring value to the business as soon as possible. Additionally, agile BI initiatives will help to engage all key stakeholders on an ongoing basis, and, thanks to self-organisation, the teams will be able to work together more effectively.
Part 2. Data Warehousing—Everything Starts with a Good Model
Why is having a data warehouse model so important? In this part of the eBook, we explore the significance of data warehouse modelling and some of our experience-based data warehouse best practices. Introducing big changes once a data warehouse is operational is difficult—hence, having a good data model can help you deliver significant returns during the later stages of development and exploitation as well as mitigate potential risks and pitfalls.
Part 3. Building Trust in Your Data—Testing Data Solutions
Data quality assurance can be a challenge, especially when working with enterprise solutions that have evolved over time. Therefore, it’s crucial to think about all the levels of the data quality testing process prior to building a new data solution. In this part of the eBook, we present various data quality testing methods, which can help you achieve the highest standards of quality in your data projects.
Part 4. The Value of DevOps in Your Data Intelligence Solutions
Wondering how to successfully employ DevOps in BI? This part of the eBook goes into detail about how to effectively apply DevOps in Business Intelligence projects, and the various benefits this can bring to your organisation. With the right tools, you’ll be able to take advantage of deployment process automation, frequent updates, and lower costs.
Part 5. Data Solutions Reinvented on Cloud
The cloud provides many value-adding capabilities—immense computational power, scalability, high availability, and many more. However, applying the DataOps approach when employing the cloud can help you to truly zero in on delivering business value in a lean and agile manner that reduces time to market. In the eBook’s last section, we explore how data and the cloud influence each other’s evolution and serve to benefit the organisation when leveraged in tandem.