Data lake

The spread of Big Data has led to a natural evolution towards Data Lakes. Sidea Group, with its specialised team of data scientists, developers and marketing specialists, offers Data Lake-based design and development services with the aim of providing deeper data analysis for data-driven strategies.

A Data Lake is a place intended for the storage, analysis and correlation of data, structured or not, in original format and from different data sources (CRM, ERP, information derived from machines in production or IoT devices).

The term “lake” identifies a data flow in its state and forms a “data lake”. They offer an unprocessed view of the data for a specific purpose.

The main feature of a data lake is to provide the ability to retrieve and organise data depending on the type of analysis you want to perform. It is a simplification compared to a Data Warehouse that requires data modelling before it is actually stored.

Advantages of a data lake:

• It does not require data structuring, on the contrary it accepts structured, semi-structured and unstructured data.

• Data is acquired in native format.

• A data lake allows you to easily configure and reconfigure new models and queries for analysis.

• It allows you to query data from a wide variety of different tools.

• Reduced storage costs thanks to its undefined structure, unlike a data warehouse where it is necessary to manage rigid databases with the consequent use of highly specialised people.

• Significant reduction in time-to-market due to the lack of data expansion and consolidation design phases.

The phases of managing a data lake are:

1. Data Ingestion and Storage: ability to capture batch or real time data and store and access unstructured, semi-structured or structured data in their original format.
2. Data Processing: ability to work on unstructured data so that it is ready for analysis with standard procedures and to engineer new data value extraction solutions.
3. Data Analysis: ability to create appropriate models to extract information from data, both in real time and on an even frequency basis.
4. Data Integration: ability to connect the Data Lake platform to applications that allow the data query and extraction in specific formats.