It isn’t a stretch to say that our society today lives in a data-heavy age, and we need help integrating it all. Forbes magazine shared a report from the International Data Corporation (IDC) that predicts that the amount of data generated worldwide will increase from thirty-three zettabytes in 2018 to one hundred and seventy-five zettabytes by 2025. As of today’s writing, that is next year!
With such a massive amount of data, enterprises hope that it will drive innovation and success in business. However, data is fragmented and can actually hold an enterprise back from achieving these goals.
Especially in human resources (HR) integration (the process of smoothly integrating HR functions, data, and processes into an organization’s overall operations). Integration in HR involves aligning HR activities with broader business goals and integrating human resource software and systems with other departments, such as payroll, finance, and talent management.
When a trusted HR company handles a business’s payroll and tax services, it allows that company to streamline its entire process, stay focused on larger organizational goals, and ensure specialists in the field are managing these critical human resource functions.
What are the effects of data fragmentation?
Sometimes when data is strewn across multiple silos, in clouds or on-premises, the fragmentation causes computer capacity to be used unproductively. Visibility of the data, which is critical for environments that must adhere to regulatory compliance, also becomes difficult.
In today’s market, businesses and organizations are overwhelmed with data. Still, raw data isn’t helpful to anyone, but this huge amount of data can be a powerful asset. Instead of utilizing it to make better business decisions, enterprises are paralyzed by mass data fragmentation.
Mass data fragmentation is a term that describes the massive amounts of secondary data that make up most of an organization’s total data volume. This secondary data includes information used for backups, file sharing, testing and development, and archiving. Such data can be stored in various places—on-premises, in the cloud, or across different infrastructures and management systems that don’t communicate with each other.
When you can’t pinpoint where your data is stored, confirm its protection, or ensure compliance, it becomes a costly and risky asset. This lack of control also hinders you from leveraging the total value of your data. According to Beta News, a survey commissioned by Cohesity and conducted by Vanson Bourne revealed that 86 percent of decision-makers recognize the importance of addressing the challenges associated with mass data fragmentation.
Moreover, many IT decision-makers feel that their secondary data is scattered across silos, making it incredibly difficult to manage in the long run. Thankfully, data integration offers a solution to this complex issue.
What is Data Integration?
From 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 the current 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 an excellent way to gather more data types and increase datasets while managing and organizing data effectively.
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 in business?
One of the oldest players in the IT world, IBM, shares how data integration works by explaining it in the following manner, “Data integration brings together information from various sources and systems, providing a unified and comprehensive view. By breaking down data silos, organizations can eliminate redundancies and inconsistencies that arise from isolated data sources,”.
Data integration has three elements:
- Different data sources (ex., third-party enterprise tools)
- The master server (retrieves data from these sources)
- Clients (those who access data from the master server)
Data integration typically kicks off when a client asks the master server for specific data. The master server then reaches out to both internal and external sources, pulls the relevant information, and merges it into one seamless dataset. Once everything is consolidated, the server delivers the unified data back to the client for their use.
How does integration help business?
Think of data integration as a versatile tool rather than a one-size-fits-all solution. It has the potential to tackle a wide array of business needs effectively. In today’s digital landscape, almost every aspect of business operations occurs online and produces data. By integrating this data seamlessly, you gain critical insights that can drive your success.
Remember the saying, “Knowledge is power”? The more comprehensive and pertinent your data, the greater your advantage over the competition. Integrating your data can provide that competitive edge, enabling you to make more informed decisions and stay ahead in the market.
Data integration helps businesses achieve a comprehensive view of their enterprise information and track patterns within it, allowing for the analysis of emerging product or service preferences and forecasting market demands.
Furthermore, data integration enhances decision-making by providing access to real-time data. With integrated data systems, organizations can quickly respond to market changes, customer demands, and internal operational needs. This agility is crucial for maintaining a competitive edge and driving growth in today’s fast-paced business environment.
Another vital benefit is improved data quality and accuracy. When data is collected from disparate sources, it is often inconsistent and prone to errors. Data integration ensures that information is consistent, up-to-date, and reliable, which is essential for making informed decisions.
Additionally, data integration supports regulatory compliance. In industries with stringent regulations, such as healthcare and finance, having a unified data system ensures that all necessary information is readily accessible and audit-ready. This not only simplifies compliance reporting but also reduces the risk of penalties.
Lastly, integrating data can lead to significant cost savings. By eliminating redundant data storage and streamlining processes, organizations can reduce operational costs. The efficiencies gained through data integration also free up resources, allowing businesses to invest in innovation and other strategic initiatives.
Benefits of implementing data integration
In conclusion, data integration boosts decision-making, data quality, compliance, and cost efficiency, making it an essential strategy for organizations aiming to stay competitive and innovative in today’s fast-paced market.