Does the datalake have an ROI? Before attempting to give an answer, let's remind ourselves of the definition of a datalake. If you're wondering "what is a datalake?" and "does a datalake have an ROI?", then this article is for you.
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What is a datalake?
The datalake: a new data storage tool to bring your company into the new age of data. datais often the technological answer to many hopes.
The promise of Big Data, the realization of more effective use cases and the drive to transform the enterprise have prompted many companies to embark on the dynamic of creating datalakes with major ambitions.
Communication around AI, process automation, the augmented advisor or marketing inflated marketingAI has helped accelerate the deployment of datalakes.
Does datalake have an ROI (or who wants to kill datalakes)?
Substantial investment in datalakes
These new data platforms represent major investments, because since the early years and the Open Source vision, the market has become more structured. Platform publishers have structured their offerings to offer a full range of security features.
After investments of over 100 million euros and several months of work for IT teams, and numerous twists and turns (RGPD compliance, security...) comes the long-awaited moment of the data feed phase.
In a datalake, data can be structured, unstructured or semi-structured for later use, in contrast to a data warehouse, which essentially holds processed, structured data.
But how profitable?
After this long waiting phase, the urgency of getting the datalake up and running means that data management practices are often forgotten, or relegated to "we'll see later".
At this stage, we have a space where all the company's data can be duplicated, at an ever-increasing cost of creation and management.
Over and above the immediate additional cost and the management difficulties posed by this rapid duplication of corporate data (need to keep information synchronized, identify the right data source, etc.), often carried out without the deployment of data governance practices, the main issue is the profitability of these platforms.
These technological solutions were created to provide a service, and thus ensure the continuity of an existing use. It's now urgent to unleash the long-awaited new uses that have been thought through over the past few weeks, and it's at this point that new difficulties arise.
The uses alternate between
- simple projects, to validate the platform and skills, but with little value added
- overly complex uses that don't take into account the company's maturity and mastery of its data assets.
The datalake and business transformation
Various studies show that 80% of uses never make it past the production stage. The long-awaited AI applications therefore seem a long way off, and the positioning of the datalake thus raises questions.
So we need to go back to basics and take a step back from technology once again. The datalake is only a means of supporting business transformation. This transformation must therefore be supported by a reflection on the business model to be deployed to support the company's transformation in conjunction with the datalake and the associated operating model.
Successful transformations of this kind require complete alignment
- the organization
- processes
- employees
- data.
This alignment is the only way to make the most of these investments and get all the company's functions working towards a common goal, offering a precise vision of ROI and enabling the costs of these new infrastructures to be absorbed.
Shall we talk about it together?
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