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!
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.
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.
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.
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!
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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!
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.
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.
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.
Master Data Management (MDM) to create your data repositories, define data quality criteria and automatically generate user GUIs.
Or API Governance, which manages and industrialises the exposure of APIs to your ecosystem (customers, suppliers, partners, subsidiaries).
Data Discovery and Data Mapping solution that puts the Data MarketPlace dimension at the heart of the Phoenix platform.
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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.