News and Events

Why DataOps should come before (and during) your Analytics and AI

Posted by Emma McMahon on 06 March 2019
Why DataOps should come before (and during) your Analytics and AI

We have all seen the flashy ads and promised benefits when it comes to enabling Analytics and AI for our businesses. Analytics and associated AI solutions are integral for the future of business, gaining you that competitive edge and we would never ever dispute this. Yet before you run out and build out your solutions, it’s time for a health check.

Why? Here is the nightmare. Imagine your new fancy dashboards aren’t showing you what’s really happening. Imagine making business decisions on projections that are false. Imagine your AI is automatically driving your business out of control through poor or corrupted information. Or forget all that and imagine the data within your organisation slowly teaching your AI bad habits and corrupting it’s learning behaviours.

Implementing a DataOps approach correctly before, during and continually after an implementation is the perfect answer to that nightmare. DataOps is the healthcare checkup that checks what is feeding into the analytics and AI solutions to ensure what they are telling you is not harmful. For example, it can be used to assess your data sources, standardise your data into a universal format, check the right data is informing the right areas, understand what data is actually needed for the business to grow and learn.

It is why a Kinaesis partnership is invaluable reassurance on your AI and analytics endeavours as we can increase the success rate on projects simply by ensuring that the result truly reflects what the business needs.

Yes, you need analytics and AI within your business. Yet you must first check your Data is healthy, correct and as detailed as possible consistently throughout the AI process. This will enable you as a business to plan, project and optimise to the highest degree.

Effective DataOps is the way to make sure the fears of ineffective and misinformed data don’t seep into reality.

DataOps Pillar: (Collaborative) Analytics

Posted by Benjamin Peterson on 27 February 2019
DataOps Pillar: (Collaborative) Analytics

Data is very valuable - and yet, it's often hard to find someone to step up and own it. We live in a moment in which the data analyst, the one who presents conclusions, is pre-eminent. It’s the upstream roles that own, steward, cleanse, define and provide data are currently less glamorous. In some ways this is a pity, because conclusions are only ever as reliable as the data that went into them.

DataOps addresses this challenge through the practice of “Collaborative Analytics” - analytics whose conclusions come from a collaboration between the analytics function and the other roles on which analytics depends. Collaborative Analytics (like everything else in the world) is about people, process and tools:

» People include the data owners, metadata providers, DataOps professionals and all the other roles whose actions affect the outputs of analytics. You have to also add into this the actual analysts and model owners themselves.

» Process includes an operating model that encourages collaboration between those roles and ensures that staff at different points in the analytics pipeline have the same understanding of terms, timestamps and quality.

» Tooling, in this case, is the easy part - any modern analytics tooling can provide sharing, annotation and metadata features that can make Collaborative Analytics a reality.

A fully DataOps-enabled pipeline would accompany analytics conclusions with metadata showing the people and processes behind those conclusions - all the way upstream to data origination.

That's a long way in the future. But what most institutions can do right now is ensure that data providers and data interpreters speak the same language.

Launch: DataOps Courses

Posted by Emma McMahon on 14 February 2019
Launch: DataOps Courses

Want to enhance your own DataOps knowledge? Want to learn how to use it to drive change across all departments? We mix our knowledge and consultancy experience to empower you. DataOps is a relatively new concept but learning it and the potential within it will give you a competitive edge.

We are launching our DataOps Courses, tailored for businesses looking to increase the real knowledge available to decision makers, deliver the user experience needed to drive value and to address sources of latency, risk and complexity in their data and analytics pipeline.

Our DataOps training will help you in the following areas:
Regulatory Compliance: Address Regulatory compliance for BCBS 239, IFRS 9, CCAR, SFTR, GDPR, Dodd Frank MiFID II, Basel III / CRD, Solvency II, AIFMD.
Optimised IT Estate: Migrate EUDAs, adopt a data-centric SLDC lifecycle, automate manual solutions, orchestrate your data pipeline to allow you to decommission legacy systems, provide a pragmatic and achievable path for Cloud/Hybrid migration.
Reporting and Analytics Delivery: Solve data issues blocking the building of Reporting, Analytics, AI and Machine Learning solutions. Solve change bottlenecks through enablement of federated delivery and iterative adoption.
Enterprise Wide Data Aggregation: Build enterprise views of core data such as Single Customer View without the dependency on building slow moving monolithic solutions. Maximise the value of your existing estate and enable clear path to simplification and consistency.
Data Governance and Control: Build pervasive data management and governance capabilities as opposed to ‘one-off’ fixes, through embedded, efficient and sustainable capability. Govern and control your data lakes whilst maintaining project agility, combine the governance and lineage into the project process and architecture of the solution.
Data Culture: Help employees understand how they can continually harness data to drive better decision-making and uncover untapped value.

2 hour workshop: walks you through the DataOps Methodology at a high level. Key takeaways: understand the six pillars of DataOps as a set of tools to measure your organisation’s maturity and plan for the future.

2-5 day course: complete with interactive exercises and case studies, the course is a definitive overview of all you need to know about DataOps. You can learn the trade secrets, pitfalls and most importantly how DataOps can benefit your progression and your organisation as a whole. This runs as either an introductory (2 day) or advanced (5 day) course depending on your level of maturity.

Provided by expert trainers with more than 60 years combined experience in delivering Data initiatives using our DataOps methodology. Not sure what DataOps is? Watch our video to understand why DataOps is increasingly growing in popularity:

If you are interested in talking more about how this can work for you, let me know if you would like to arrange a chat! If you are interested in seeing more content and tasters you can sign up for DataOps Course updates here.

For more information please click here.