Modern society lives in a data age. A report from IDC predicts that the amount of data generated worldwide will increase from 33 zettabytes in 2018 to 175 zettabytes by 2025.
This is a huge amount of data, and enterprises hope that it will drive innovation and success in business. However, data is fragmented and can actually hold you back from achieving these goals.
Is Data Fragmentation Holding You Back?
Today’s businesses and organizations are drowning in data, but raw data isn’t useful to anyone. This huge amount of data can be a powerful asset, but instead of utilizing it to make better business decisions, enterprises are paralyzed by mass data fragmentation.
Mass data fragmentation refers to the vast amounts of secondary data which typically comprises the majority of an organization’s total data volume. Secondary data pertains to data used for backups, file shares, testing and development, and archiving stored in on-premise locations, in the cloud, or in infrastructure silos or management systems that don’t integrate.
When you don’t know where data is stored, if it’s protected or if it’s in compliance, data becomes costly and risky, and you’re prevented from fully utilizing its value. More than 900 IT decision makers feel that their secondary data is scattered across silos, and is or will become extremely difficult to deal with in the long term, according to a research Vanson Bourne did for Cohesity.
Fortunately, there’s a solution to data fragmentation: Enter data integration.
What is Data Integration?
According to Wikipedia, data integration involves combining data residing in different sources and providing users with a unified view of them. This process becomes significant in a variety of situations, which include both commercial and scientific domains.
In an age of fragmented data, data integration makes data useful to organizations by consolidating data from various sources into a single, unified system and then organizing it and making it consistent. Data integration is a good way to gather more data types and to increase datasets all while managing and organizing data effectively.
What is data integration example?
For example, customer data integration involves the extraction of information about each individual customer from disparate business systems such as sales, accounts, and marketing, which is then combined into a single view of the customer to be used for customer service, reporting and analysis.
Data integration aims to provide its users with consistent access and delivery of data to meet the information needs of all business processes and applications. In other words, data integration allows decision makers to view the most in-depth representation of relevant data so they can steer their organizations toward the achievement of business objectives.
An example of what data integration looks like is migrating an enterprise’s marketing system and customer database into a new CRM that handles both. This enables more efficient business operations.
Where is data integration used?
Data integration initiatives — particularly among large businesses — are often used to create data warehouses, which combine multiple data sources into a relational database. Data warehouses allow users to run queries, compile reports, generate analysis, and retrieve data in a consistent format.
How Does Data Integration Work?
Data integration has three elements:
- Different data sources, such as third-party enterprise tools,
- A master server which retrieves data from these sources, and
- Clients who access data from this master server
Data integration generally begins when a client requests certain data from the master server. The master server, in turn, extracts data from internal and external sources, consolidates the gathered data into a single, cohesive dataset and then serves back the collected data for the client’s use.
Benefits of Data Integration
Data integration offers businesses several advantages. These benefits include:
- Make data more available to more people
A centralized system enables any employee to retrieve, inspect and analyze data, and data that’s easily accessible can be easily transformed. Employees can use this data in individual, team or inter-departmental projects, enabling sharing of knowledge among people within the company.
- Reduces data complexity
When employees have so many applications, you can expect that the number of potential interfaces is exponentially as many as the applications your organization has. You’re bound to get entangled by the complexity of the data if your company doesn’t have a data integration plan in place, for instance, a data hub that employees can publish and subscribe to. With data integration, data is streamlined and delivered efficiently.
- Decreases errors
Because raw data can’t be used, data integration cleans, validates and organizes information so that only those that are accurate, high quality and robust can pass through. This translates to data that’s free of duplication, inconsistencies and errors. Data integration solutions also include regular reporting so that any issues are identified and repaired easily in real time.
- Saves time and resources
With data integration, enterprises can significantly cut the time it takes to prepare and analyze data. Data integration can save time and resources that would otherwise have been spent on manually gathering data, building from scratch or hand-coding. These savings in time and resources can be spent and put to better use elsewhere.
- Streamlines operations and improves efficiency
Data integration allows employees to access unified data and eliminates the need for manual data gathering, i.e., logging into multiple accounts to view different datasets. This improves overall business operations, and the data that they need is more easily available and more reliable.
With access to relevant and accurate data, managers can create standardized processes or improve common workflows to help workers easily perform tasks with quality results. Data integration can also help managers identify and resolve any issues.
- Delivers more valuable or high-quality data
When data is integrated in a centralized system, i.e., disparate datasets are combined or brought together in a unified view, it’s easier for employees to identify errors or other issues in the data and implement the necessary improvements. This results in more accurate data, which will improve the value of the data over time.
- Makes collaboration easier
A centralized system or unified view of data makes collaboration between departments easier. This cooperation boosts business intelligence as it facilitates a more complete and structured understanding of data.
- Aids in smarter decision making
With access to more data, decision makers will be able to better understand and navigate through any business situation. With the help of more in-depth and relevant data, decision makers can better lead their teams toward department or corporate objectives.
- Keeps data current
With integrated data, it’s easier to keep information current or up to date. You can even update data real-time if you’re using a server or cloud solution.
- Creates a better employee experience
With access to unified data, employees can perform better in their jobs. Because of this, they will be more fulfilled, and this is important because exceptional employee experience translates to exceptional customer experience.
Data Integration Helps Businesses Succeed
Although data integration isn’t a “one size fits all” solution, it can address numerous business needs. Today, nearly all stages of a business operation happen online and generate data, and data integration can provide you with all the clues you need to succeed. And because “knowledge is power,” the more complete and relevant data you have, the more edge you have over the competition.