What is Data Integration?
To understand what a data integration platform is we first need to understand what exactly data integration is and how it usually works, by definition:
“Data integration is the process of combining data from different sources into a single, unified view. Integration begins with the ingestion process, and includes steps such as cleansing, ETL mapping, and transformation. Data integration ultimately enables analytics tools to produce effective, actionable business intelligence.”
Basically, a data integration process requires a network of data sources, a master server, and clients accessing the master server. The basic process is, the client sends a request to the master server for data. The master server then intakes the needed data from internal and external sources. The data is extracted from the sources, then consolidated into a single, cohesive data set. This is served back to the client for use.
What is a Data Integration Platform?
Now that we have a clear understanding of data integration, we can get a better understanding of what is a data integration platform, by definition:
“A Data Integration Platform is primarily used and governed by IT professionals. It allows data from multiple sources to be collected, sorted, and transformed so that it can be applied to various business ends or routed to specific users, business units, partners, applications, or prospective solutions.”
Basically, the primary function of a data integration platform is to merge and centralize data for ease of use, management and business intelligence.
Data Integration platforms use extract, transform, load (ETL) tools which are designed to pull data from source systems. The mechanisms provided by these ETL tools are change data capture, slowly changing dimensions, hierarchy management, data connectivity, data merging, reference lookups and referential integrity checks. Data integration performance has increased significantly by utilizing memory, parallelism and various data transport architectures.
There is also a variant of ETL tools used with some platforms, which is called extract, load, transform (ELT) tools which eliminate the need for a separate application server dedicated to ETL and can be deployed at either the data sources or target systems based on their capacity and configurations. These tools are used to store raw data for user and then transform it or its subset for specific business intelligence and analytics application.
There are three common types of data integration platforms:
- Cloud-Based Data Integration Platforms:
Cloud-based Integration Platforms as a Service (IPaaS) are increasingly popular given their adaptability and relative cost-efficiency. An IPaaS is easily scalable, has cheaper maintenance, and can be adapted or upgraded without disruption.
- Built from Components:
Data integration platform components can be added to preexisting business processes, allowing data to be transferred seamlessly. These platform components can be purchased from technology providers that specify in data integration.
- Installed Data Integration Platforms:
These platforms work like a software installation into a pre-existing business process.
Problems Solved by Data Integration Platforms:
Data integration platforms have been improving and refining their tools over the past few years and some of the solutions provided by them are as follows:
- Low-Impact Change Data Capture
- Ease of use
- Packaging various ETL tools
- A unified data integration platform for the agile enterprise
- Cloud based platform solution
- Provide data integration, data quality and data governance solution
- Simplify Business Intelligence (BI)
- Big data integration
- Data migration and consolidation
Why use Data Integration Platform?
Now coming onto the main question, why should you use data integration platforms? To answer this question, we need to understand the importance of data in the world right now, which is quite important because every business decision may it be small or huge, is based on the data being provided with it. If the data is insufficient it leads to poor decision making, which in turn may lead to failure and in this progressing world failure is not an option. Hence, data is important.
The data integration platforms are basically a packaging which provide ETL (extract, load, transform) tools and databases which are used to get data, store it in different sources and provide the data when requested in a presentable form. Hence, specialists are trained in handling this software so that they can properly manage their business intelligence.
Now coming onto the answer since these platforms are a packaging, they provide multiple tools in the same environment so you don’t have to look for specific tools for different tasks and because of the low-impact data change capture you are provided a log (i.e. a type of version control) which keeps track of all the changes done on the data and where is the data being kept or referred from (i.e. source of data).
Since data is quite important and is increasing, data integration platform not only provide the tools to extract and maintain data they also provide tools to integrate into your business which in turn increases efficiency and reduces time for making decisions, to serve your customers better and identify areas of improvement. Please feel free to reach out to us (firstname.lastname@example.org) regarding our data integration platform offerings.
As always, we would love to hear your feedback.