Data Architecture

Setting up a Data Lake is vital for companies seeking competitiveness.

Why a Data Lake?

A data lake offers your company a solution to add value to your data, promoting innovation and operational efficiency. Aqsone supports you in its implementation. In 5 steps.

1

Choose the type of platform

Many companies choose tohost their data platform in the cloud, which is now becoming the norm. These solutions make it possible to size the capacity of the data platform according to uses, which offers great flexibility and limitless agility.

2

Collect and ingest data

It's necessary identify data sources and set up ingestion processes to collect data reliably and efficiently. This involves setting up data pipelines and configuring automated data flows.

3

Store and manage data

Once the data has been collected, it must be store in such a way as to facilitate their access and subsequent use. This requires the implementation of scalable data storage structures, backup strategies and recovery in the event of data loss.

4

Ensuring data quality

The data stored in the Data Lake must be high quality, reliable and safe so that the analyzes are relevant. It is therefore important to put processes in place to monitor and improve data quality.

5

Check security and compliance

The data stored in the Data Lake is sensitive and must therefore be protected. It is important to put security measures in place to ensure the confidentiality, integrity and availability of stored data. Compliance with regulations such as GDPR must also be considered.

A Data Lake? Not without data governance.

Data governance involves defining the policies, standards and practices to manage the data stored in the Data Lake, including access, permissions, security and privacy.

Technologies that we master

Amazon Web Services

AWS offers a complete range of products for processing your data: Amazon S3 (storage service), AWS Glue (ETL service), Amazon SageMaker (machine learning service) or even Amazon QuickSight (dashboarding solution)

Microsoft Azure

Azure offers a wide range of solutions to manage your data: Azure Data Lake (storage service), Azure Data Factory or Azure Databricks (ETL service), Azure Machine Learning (machine learning service) or even Power BI (dashboarding solution)

Google Cloud Platform

GCP offers a wide range of solutions for managing your data: Google Cloud Storage (storage service), Google Cloud Dataflow (ETL service), Google Cloud AI Platform (machine learning service) or even Google Looker Studio (dashboarding solution )

Palantir Foundry

Palantir offers an advanced platform for managing your data: Palantir Foundry (storage service), Palantir Foundry Transform (ETL service), Palantir Foundry ML (machine learning service) or Palantir Contour or Dashboard (dashboarding solution)

Do you want to set up your Data Lake? Let's talk about it !