Businesses now compete to quickly and effectively extract valuable insights from their datasets to create better services, goods, and, ultimately, experiences. A Data Integration Platform collects data from various sources and sorts and transforms it to be applied to multiple prospective solutions.
What is Data Integration?
Data integration is the process of integrating data from multiple sources to increase its value. For instance, you may generate a 360-degree picture of your customers by connecting data from your CRM, contact center, website, marketing, mobile app, and sales tools.
Having a 360-degree perspective of the company (and, eventually, the customer experience) is more beneficial than understanding individual data points that do not seem to correlate in each of the systems.
Thus, data integration is about increasing the use and value of data inside an organization. Data must be used to improve business intelligence or operational analytics. Both of these factors ensure more strategic judgments for your business growth.
6 Reasons For Why You Should Consider A Data Integration Platform
Let me ask you a few questions,
- Want to establish your apps as a reliable source of truth for the whole business?
- Want to enhance your analyzing, forecasting, and predictive analytics capabilities?
- Want to develop a 360-degree vision of your consumer and business?
- Want to accelerate innovation and speed to market?
- Would you want to improve your agility and responsiveness?
- Want to maximize the return on your technology stack investments?
If you responded yes to at least one (or all) of these questions, you’ve come to the right spot.
Data integration is critical for fostering deeper collaboration and automating business processes and workflows in real-time, reducing human effort, and fostering the sort of company that provides outstanding experiences.
Whatever stage of digital transformation you are at, data integration is vital to success.
It’s Okay To Be Struggling With Your Data
Almost every organization has attempted to digitally convert and leverage the potential of their data in the modern day. However, it is very uncommon for individuals to continue to struggle.
With vast volumes of big data created, the quick speed of technological innovation, the high cost of change, and a myriad of business analytics tools accessible, it’s easily understandable how so many businesses are struggling to extract value from their data.
Without integration, data stays isolated in silos. Manually collecting data from each system or program, copying it, reformatting it, cleaning it, and finally analyzing it requires a great deal of labor.
Due to the duration of this process, the data may become old and useless by the time the analysis is complete. While it is critical to integrate your business’s data, several data integration solutions are available.
Let us go a bit further.
Read More: Cloud Enablement Services: Everything You Need to Know
What are the Different Types of Data Integration?
Describe the process of migrating data? The term “data migration” refers to transferring data assets from one location, format, or application. For example, this word is often used when data is transferred from an on-premise database to a cloud-based database. However, data migration encompasses three distinct processes: data storage transfer, cloud migration, and application migration. It’s all about transferring data, not improving its utility. While you will have easier access to moved data, you will not get more insights.
Master Data Management
Master data management (MDM) is a term that refers to the management of master HazenTech is concerned with establishing a standard set of rules, definitions, ownership, and responsibility across IT and all other parts of the company for the organization’s most critical shared data assets. These assets are referred to as master data and often include customers, suppliers, and locations. Getting everyone on the same page about using this data is critical to working as a whole.
Enterprise Application Integration
Enterprise application integration (EAI) is a term that refers to the process of integrating business applications. As the name implies, EAI establishes interoperability between systems and applications. This is the section where you configure Workday, Salesforce, Redshift, ServiceNow, and Oracle to work together harmoniously. EAI is crucial for omnichannel customer interactions, optimizing workflows and procedures, and ensuring that consumers and workers have a seamless experience.
What is an aggregation of data? This is the process of collecting and assembling data to store it in its raw state or prepare it for analysis. Three distinct forms of data aggregation exist.
A data federation establishes an integrated picture of data by establishing a virtual database that does not store data but contains information about the location of the data. The data federation provides a unified view of the data but does not store it.
A data lake is a repository for large volumes of unstructured data that has not been assigned a purpose or readied for use. Although this data may or may not be utilized in the future, it is preserved and retained for its future usefulness.
Finally, let’s discuss data integration in a data warehouse.
Data warehousing is the process of storing structured data from many sources for analytics and business intelligence. Data is extracted from many sources and loaded into a data warehouse (AWS Redshift, Microsoft Azure SQL Data Warehouse, Snowflake, SAP Data Warehouse Cloud, or Oracle Database Cloud Service) to report business intelligence and data virtualization.
HazenTech is a data integration platform designed to make data integration smarter, quicker, and more straightforward. With over 500 pre-configured Snaps, your business teams and developers can combine data and apps with a few mouse clicks rather than writing code.
Our team at HazenTech makes validated suggestions and gives direction for more intelligent integration. Get in touch with HazenTech and allow us to help you to make more intelligent organizational decision-making.