Case study

Market data ingestion for data lakes

Simplifying market data processing to companies like Accenture and Fractal.

The popularity of data lakes is exploding as organizations are transitioning their data warehouses and other systems to the new efficient and collaborative cloud environments. Data lakes can store any type of data, either structured or unstructured, therefore companies can use them to host much wider scope of information than ever before.

One of the largest food manufacturers was struggling with the integration of panel data into their data lake system. This type of data cannot be processed in a raw format and requires customized solutions for handling hierarchies, masking rules, non-additive metrics and so forth. As a result, many questions arose about the best way of integrating data-feeds from different agencies, adding common layers to harmonise them and the actual process of moving them to the data lake.

Redslim partnered with this organisation to resolve all those issues, from collecting the data, enriching and formatting it, all the way to making it available for direct ingestion to the data lake on an ongoing basis. We successfully cooperate with Accenture, the data lake partner of choice, properly structuring the data and providing advice about how it should be used for visualisations.

Currently, we keep delivering 48 databases from 20 countries with both panel and EPOS data, with possibilities of further expansion. Redslim ensures a consistent stream of market data deliveries, sourced from all the different agencies that our client works with in the local markets.


 

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Eric Bensimon
eric.bensimon@redslim.net
+33 6 23 89 73 85

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Our purpose is to help companies activate their data assets better

We enable you to access and use the information assets you already have, by federating existing information using Business Intelligence. We support you in all phases and provide you with knowhow and foresight while advising you every step of the way.

 

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Think of aggregating market data in Office, Power BI, or other reporting and visualization tools.

 

Or to simply transforming your data sets into a known format ingestible in your available front-end.

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