To become a data-driven enterprise: we all want it. What’s more, it’s a must for every organisation. But how do you do that? Data visualisation and data science only lead to valuable insights if you manage your data correctly. With DataOps, you build solid foundations and manage your data throughout its entire life cycle – so users can quickly get to work with correct data.
Data is the raw material of any data-driven enterprise. Today, these resources come from a wide variety of sources – from sensors, smartphones, social media and ERP systems to open-source software; on-premise or in the cloud. What’s more, the mass of data is growing explosively. To be able to analyse your data smoothly and extract valuable insights from it, it is crucial to manage your data intelligently at every step: from the moment you collect, store and process your data to making it available to users. And that’s a complex process.
To be able to analyse your data smoothly and extract valuable insights from it, it is crucial to manage your data intelligently at every step of the life cycle.
Data management = production process
DataOps combines users, processes and technologies to create a reliable, high-quality data pipeline that any user can easily translate into insights. Compare it to a factory that processes raw materials into finished products:
DataOps combines users, processes and technologies to create a reliable data pipeline that you can easily manage.
What do Ordina’s DataOps experts do for you?
Things can go wrong in every step of your ‘data life cycle’. Along the way, data can be damaged, bottlenecks can occur, data sources can conflict and/or there can be duplicates. Once in the ‘factory’, the quality of the data pipelines must be monitored, all data must be centralised and catalogued and processes must be automated to ensure that your data generates value. DataOps helps you:
- monitor the quality of your data: analyses, classifications, version checks, comparison of data sets, automatic tests, etc. ensure qualitative data.
- find the balance between centralisation and freedom: depending on your needs, you determine which aspects of data management and analytics are centralised – and controlled – and when users can start working with their data themselves (self-service).
- organise and structure the data in a catalogue: thanks to a catalogue, all users can easily find the data they need for analytics.
- automate the data pipeline: by automating tests and checks and automatically generating code, you reduce the margin of error.
- monitor security and privacy: audits, authorisations, checks, encryptions, etc. ensure the necessary security and privacy.
- continuously monitor and improve your data management: through continuous monitoring and reporting, data management will be constantly adjusted and enriched – to meet your rapidly changing data needs.
Agile is also the way to go in DataOps
Just like a production process, your data pipeline is constantly changing. By constantly updating and adapting your data management (deleting, adding to, replacing, etc. data sources, applications, etc.) you ensure robust, agile data management – so you can respond quickly to changes in the environment.
DataOps works in an agile way. So you can be sure of robust, agile data management, allowing you to respond quickly to changes in the environment.
- You get the best solution, experience and expertise
Our DataOps team consists of experienced and enthusiastic experts with a variety of backgrounds: analysts with a business background who understand your story, IT professionals who are responsible for the technical part, etc. They know what data has to do, know the technology and have experience with data projects in a wide variety of organisations.
- You can count on the backup of a multidisciplinary team
DataOps doesn’t happen in isolation. We work closely together with our data visualisation experts and data scientists and also join forces with colleagues from other business units. For example, we can integrate your data with your existing IT systems or take certain security or privacy aspects into account.