Simultaneous implementation of the SOLOCHAIN Warehouse Management System (WMS) in 5 distribution centers View the press release

Data Analytics, Supply Chain
June 15, 2017

Data lake: the data storage revolution

One of the major current challenges of Big Data is being able to store and effectively exploit sufficient volumes of data. In order to perform well, artificial intelligence (AI) and machine learning applications need large volumes of data. However, storing this information often comes at a high price. How can we store this information in the best possible conditions but at the lowest cost? Spotlight on Data Lake, new cloud-based technology revolutionizing Big Data.

Article

What is Data Lake?

With the rise of Big Data, the volumes of available data have gone through the roof. Problem: Because of costs, companies cannot extract and use all data from software as easily as they used to.

To more effectively store data over the long term, a new type of technology was needed. This is why Data Lake was developed. It is a storage solution that allows you to organize data files in their original formats without having to convert them.

Why use Data Lake?

Storing data sets from Big Data is today a real challenge for companies. Artificial intelligence algorithms need to analyze a large amount of information in order to study behaviors and establish models and reliable forecasts. As such, we need to ensure that data is secured and can be accessed over time without causing storage costs to blow through the roof.

Thanks to Data Lake, storing a large volume of quality data, which will be used to feed AI data exploitation tools, is child’s play. The aim of the operation: to easily build predictive models. This new storage technology responds to the 3 main requirements of Big Data:

  1. ensure data security;

  2. preserve data integrity;

  3. guarantee data availability over time at the lowest cost.

A Data Lake designed by Generix Group

In order to exploit data generated by Supply Chain solutions (WMS, TMS, Order Tracking), Generix Group has designed its own cloud-based Data Lake solution. This technology enables companies to:

  1. improve warehouse planning;

  2. feed predictive analytics engines and models;

  3. import data into Business Intelligence or corporate Data Lake solutions;

  4. build datavisualization applications based on a completely integrated solution.

With its Data Lake, Generix Group aims to offer its application users an unlimited and 100% secure solution at the lowest cost when compared with conventional storage solutions.

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