Too often, companies begin their New Data Platforms in the Cloud and forget that the challenges extend beyond analytics. This is especially true with the anticipated wave of “voice analytics,” where voice interactions could quickly replace dashboards. However, these new data platforms, referred to as “Data Lakes” here for simplicity (purists may disagree), can become a natural pivot for the information system (IS) of tomorrow. In this article, we delve into this not-so-revolutionary concept, examining its impacts and promises for the world of data.
Definition of an “Active” Data Lake
Contrary to the traditional data warehouse, often perceived as a “dead end” for data, the active data lake is dynamic and interactive. Data is not only stored but also transformed and enriched within the lake. As a result, this dynamic environment makes it vital for the rest of the IS, powering real-time applications. Therefore, it becomes an “active” element of the IS.
Reduction of Redundant Interfaces
The active Data Lake minimises the need for multiple application interfaces. This simplifies the IS architecture and optimises processes. Many organisations have realised that the same management rules or data transformations are often implemented within ETL, EAI, or other interfacing solutions.
What Does an Active Data Lake Change?
Design and Implementation
Designing an active data lake requires a holistic approach that integrates storage, processing, and access needs. Above all, agile modelling is essential, adapting to the company’s needs. Finally, the new family of solutions called Reverse ETL will be invaluable.
Monitoring and Data Quality
Continuous monitoring and data quality management are crucial to ensure data integrity and relevance. The concept of Data Observability becomes more important than just data quality, enabling a rapid response to data issues.
Uses and Benefits of an Active Data Lake
- Data unification: Raw and enriched data is centralised, allowing uniform management and transformation.
- Application innovation: Develop a new range of applications based on Data Lake data, opening the way to new services.
- Partial migration of IS components: If IS components connect via an active data lake, migrating a single component becomes simpler.
Practical Use-Case
A large retailer recently consolidated thirteen different checkout systems. They achieved this by developing data flows into their Data Lake, which then served as the interface with other application systems (finance, marketing, operations, forecasts, etc.). This example highlights the practical benefits of an active data lake.
The Data Lake as a Single Source of Truth
With its enriched and centralised data, the active Data Lake positions itself as the single reference for all information within the organisation. This marks the beginning of a truly data-driven era.
Conclusion
In short, active data lakes are not just a trend; they are transforming data management. They are evolving yesterday’s data warehouses into dynamic hubs where data is actively used in real-time.
If your company hasn’t embraced this approach to data management, it’s time to join the movement! These points for reflection, each deserving further investigation, will hopefully convince you to take the right path for your new data platform.
Devoteam helps you transform your data management.
With a team of 1,000+ data consultants with over 960 certifications across leading cloud platforms like AWS, Google Cloud, Microsoft, DataBricks and Snowflake, Devoteam helps you design and implement your active data lake solution.