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Avanade’s Daniel DeMarco discusses the importance of modernising your data management platform and how to do it effectively.
Organisations collect data with every operation and customer interaction. According to a 2017 study, 2.5 quintillion bytes of data are generated every day.
The growing availability and volume of data combined with the emergence of more efficient analytics tools have created opportunities for companies to develop data platforms that provide mission-critical insights, fuel new revenue streams, and provide points of transformation for customer and employee experiences beyond cost-reduction initiatives. The prevalence of these platforms has made it increasingly more important for organisations to find ways to make effective use of their data.
For organisations to keep up, they must develop and evolve data platforms that enable fast, reliable insights. Cloud computing and modern analytics tools offer enterprises the ability to bring data together from across business units and geographical boundaries to take advantage of AI to learn more about their business, customers and industry.
Effective data management is foundational for success, and a robust data supply chain will become a requirement for companies looking to thrive in today’s business landscape.
What does a modern data platform look like?
Traditional data platforms lack the speed, flexibility and scalability to deliver fast insights. They are constrained by physical infrastructure limitations, siloed operations and the inability to evolve. Traditional IT departments are struggling to keep up with the daily enhancements found with cloud capabilities.
Modern data platforms are characterised by fast, fault-tolerant infrastructure, a high degree of collaboration and the ability to process a high volume and variety of data. They allow for self-service business intelligence and predictive analytics.
A modern data platform harnesses the power of cloud computing to optimise data availability, scalability and usability, and takes advantage of modern data processing tools to help answer the most pressing questions for your business. These technical shifts alone do not make a modern data platform produce instant results. However, these capabilities combined with new questions and insights provide the fuel for those new revenue streams and customer impact much desired today.
Modern data platform in practice
An effective data management solution covers the lifecycle from data source to actionable insight. This includes identifying data sources, ingesting, cleansing and storing data, training a model and serving insights to end users.
The source is data that has been collected by the organisation. The ingestion is the process of bringing the data into the platform. The data storage solution should enable efficient retrieval. The processing requires an engine for data engineering and machine learning. Finally, training a model and serving insights enables analysis and discovery.
The value of the modern data platform is not the outcome, but rather the variety of business use cases, the value points and the shift to becoming a data-driven organisation that creates a future-ready organisation. There are a variety tools and architectures to support the specific data needs of each organisation.
Making the change
Modernising a data ecosystem isn’t always easy. It involves crafting a comprehensive data strategy, introducing fresh processes and implementing new tools. Cloud data tools are designed in a way that allow organisations to start small and then scale up as the organisation becomes ready to adopt the upgraded processes. For companies undertaking initiatives to modernise their data platform or introduce new functionalities, it is often best to take a value or design-led approach.
It is important to assess the contribution of each new feature to the overarching data strategy and gauge the ability of the newest features to evolve with technological advances and scale with more data inputs.
Creating a strong data strategy and roadmap acts as a foundation for all your data modernisation initiatives. The initial steps on a data modernisation journey include identifying the insights, operational enhancements and broader business initiatives that could provide the most value to your business, and crafting a data strategy that will allow you to meet your goals in those areas. That means defining a clear vision of where you want to go and generating a strategy that will allow you to get there.
Daniel DeMarco is a member of Avanade’s analytics team in New York. A version of this article originally appeared on the Avanade Insights blog.
