DOSSIER

Choosing your Data Platform. Our guide from definition to use cases and selection criteria!

The Data Platform: the foundation for collecting, enhancing and bringing to life all the data within your organisation, and transforming it into decisions and insights. Unleash the potential of your data!

What is a Data Platform?

In practical terms, what is a Data Platform?

The role of a Data Platform, or EDP (Enterprise Data Platform), is to centralise the collection of a variety of data, optimise its storage and manage its processing so that it can be used throughout the organisation. In this way, a single data platform can be used throughout the organisation, avoiding the creation of information silos!

Its architecture is designed to enable interoperability with other systems, adapt to increasing volumes of data (and users), and offer intuitive interfaces. In doing so, it supports business decision-making processes by providing relevant information in near-real time.

Because they manage “traditional” files and databases, as well as more complex solutions involving Big Data, Data Platforms are the vectors that feed information systems (IS). They are therefore vital. With the development of the Cloud, Data-Driven strategies and the IoT (Internet of Things), use cases are multiplying, and platforms need to keep pace by adopting a Modern Data Platform approach.

How does a Data Platform work?

A Data Platform refers to a technological infrastructure integrated into the information system, the main objective of which is to consolidate and transform raw data into usable information, to guide organisations’ decision-making, and also to facilitate the use of data by business tools and users. To do this, it integrates data from multiple sources, cleansing and structuring it to ensure its quality and consistency, and putting it to work for business processes and internal customers. Here are the main principles that govern it:

It's the tool's ability to bring together information from a variety of sources, such as internal databases, SaaS systems, real-time feeds, log files, IoT sensors and so on.

This involves implementing solutions such as data lakes, repositories or data warehouses to store data securely and on a large scale. More specifically, data lakes are used to store unstructured or semi-structured data, while data warehouses are optimised for structured data and complex queries.

These are data processing functions for cleansing, normalising, enriching and transforming data. These are known as ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) technologies.

It includes reporting, business intelligence and, potentially, AI-based approaches (data mining, machine learning, etc.) to discover trends and patterns and gain insights.

In other words, the mechanisms that ensure quality, regulatory compliance, flow supervision and data security, such as access management, encryption and audits.

This is the ability of a platform to integrate and operate with other systems and applications, an essential element in ensuring the smooth flow of data throughout the organisation.

This is the ability of a platform to adapt to variable (often growing) data volumes and to support changing workloads, often via Cloud solutions.

Intuitive interfaces and unified data visualisation tools are essential if both technical and non-technical users are to work quickly and easily.

Behind the notion of intelligence, the realities can be very diverse! The foundation is automation, whether in the integration, transformation and distribution of data or the processes that bring it to life. It also includes Business Intelligence approaches, including the use of Machine Learning and other AI approaches, for example, to understand and classify information, and to map and catalogue data automatically.

Focus on: Data Integration Platform vs Data Platform

Although the terms data platforms and data integration platforms are sometimes used interchangeably, they cover different scopes – that of data platforms encompassing integration! While a data platform represents a centralised architecture that manages, circulates and analyses dispersed data, a data integration platform focuses primarily on the circulation of this disparate data between the various applications of the Information System. It then prepares it for analysis, acting as an intermediary that facilitates the routing and transformation of this data between all the systems, but without storing or analysing it directly.

What are the use cases for Data Platforms?

The use cases for Data Platforms or EDPs are mainly related to data governance within the company or in certain business areas. They support the organisation’s data strategy by providing tools and guaranteeing data centralisation, consistency and quality. In doing so, they can also be used to meet specific business challenges and needs!

In the public sector

  • Centralising, analysing and improving the quality of data relating to local authority staff and teams
  • Integrating, consolidating and securing public health files
  • 360° management of contractual data
  • Implementation of user repositories and personalisation of the citizen experience
  • Consolidating data and setting up an open data portal for natural and environmental resources
  • Data Platform for HR data integrating administrative workflows
  • Data platform to improve citizen services (portal, processes, repository, open data)..

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In companies

  • Optimisation of the supply chain by building a consolidated view of all data (ERP, WMS, PLM, etc.)
  • Data platform for all supplier information, with integration of a supplier portal
  • Integration of customer data for a 360-degree view through a CDP (Customer data platform)
  • Mapping, cataloguing and compliance of all the organisation’s data
  • Consolidation of consumer trends and preferences with the product repository to adapt offering strategies
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Understanding the role and benefits of a true Data Platform

Enterprise Data Platforms are drivers of operational optimisation, offering advanced personalisation of services and agile coordination of flows and repositories, while ensuring the supervision, compliance and security of data and its circulation within the information system.

However, there is a wide diversity of vendors, solutions and technologies behind the notion of a Data Platform. In fact, many software publishers have built their data platform by starting with one brick (integration platform, MDM, BPM, etc.) and successively developing or acquiring other solutions. The completeness of the scope, as much as the transparency of the pricing or the coherence of the various platform components, are therefore essential if the solution you choose is really to meet your challenges!

Criteria for choosing a Data Platform

  • Diversity of integration approaches (ETL/ELT, ESB, etc.) to adapt to all data transformation and circulation challenges.
  • Interoperability and connectors: for exchanging data with other systems and applications.
  • Modelling and digitisation of IT and business processes, because a Data-Driven approach means managing processes.
  • Analysis and processing capabilities: advanced tools for analysing, reporting and processing data.
  • Data governance and master data administration: to guarantee data quality, compliance and centralisation within the platform.
  • Ease of use and administration: intuitive UX and UI and simplified administration options to facilitate day-to-day management.
  • Sophisticated native supervision to control all flows.
  • Simple, transparent pricing, both initially and as usage evolves.

The benefits of data platforms

  • Data accessibility: bring together data from multiple sources in one place, making it easier to access and share information.
  • Control of your company’s data assets and compliance of the organisation’s data
  • Development of data acculturation within the organisation by making information available to the business lines, and creating perceptible value in the day-to-day lives of employees.
  • Cost reduction: to reduce the costs associated with data management, integration and consolidation.
  • Operational efficiency: by automating integration workflows and a number of low-value tasks, as well as speeding up and better managing business processes.
  • Improved decision-making: consolidating and enhancing the quality of data provides insights to guide strategic and operational decisions.
  • Compliance: implementing robust data governance makes it easier to comply with data protection regulations and industry standards

The Blueway Phoenix platform and our convictions

Our Phoenix platform is designed to be as comprehensive as possible, covering the entire spectrum of data management within a single, coherent solution. From urbanisation to facilitate the circulation of data with the application bus or ESB, quality processes and the implementation of repositories thanks to MDM (Master Data Management), the digitalisation of business processes with BPM (Business Process Management) and BPA (Business Process Automation), the Data Catalog for the creation of data sets and API Management for the openness and interoperability of the ecosystem, Blueway offers the richest and most complete European data platform on the market!

With such comprehensive coverage, we are convinced that Blueway offers the best approach to the Data Platform concept. We are convinced of the fundamental role played by the processing, transport, manipulation and governance of data, for the benefit of business and corporate processes. This idea, represented by the Data Platform concept, can only be achieved with a single, centralised system that provides a bridge between Data and Process, and thus places people at the heart of the Information System.

Phoenix by Blueway: the richest European Data platform on the market

ESB

The Enterprise Service Bus (ESB) is dedicated to the transport, manipulation, control and display of data, within an SOA logic. It is the key to interoperability and optimised management of data flows.

BPM

Business Process Management (BPM) for mouse-based modelling of your business processes, in compliance with the BPMN2 standard, and distributing them throughout the organisation, in line with the IS.

MDM

Master Data Management (MDM) to create your data repositories, define data quality criteria and automatically generate user GUIs.

APIM

Or API Governance, which manages and industrialises the exposure of APIs to your ecosystem (customers, suppliers, partners, subsidiaries).

Data Catalog

Data Discovery and Data Mapping solution that puts the Data MarketPlace dimension at the heart of the Phoenix platform.

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Our latest content on data management

Our FAQs on data platforms

Enterprise data platforms use various methods such as encryption, identity and access management, and continuous monitoring to protect data against unauthorised access and security threats.

Cloud-based data platforms offer greater scalability, flexibility and efficiency, reducing infrastructure costs and facilitating access to technological innovations.

A data lake is a vast reservoir of raw data stored in its native format, while a data warehouse stores structured and filtered data for a specific analysis purpose.

Data governance involves putting in place policies, standards and procedures to accurately manage data throughout its lifecycle, ensuring data quality, compliance and ethical use.