Big data, combined with modern analytics, provide virtually unlimited opportunities for process optimization and also open up new opportunities for scientific research. Check the most important data management frameworks in the article below.
What is data management?
Data plays an important role in the operation and functioning of any business. Companies need to be able to extract information from data and find valuable insights, separating them from the “noise” that creates various systems and technologies that support today’s highly interconnected global economy. Thus, the role of data cannot be overestimated. But the data itself is useless. Companies need an effective strategy, strategic management, and data management model to use all forms of data for practical and effective use in supply chains, employee networks, and customer and partner ecosystems – and that’s not all.
Working with big data is not like a typical business intelligence process, where simply adding together known values yields results: for example, adding bills paid together becomes sales for a year. When working with big data, the result is obtained in the process of cleaning them through sequential modeling: first, a hypothesis is put forward, a statistical, visual, or semantic model is built, and on its basis, the correctness of the hypothesis put forward is checked, and then the next one is put forward.
A database is an array of information that we regularly refer to and do not even notice. For example, you log in to a social network or simply upload a picture to the site. In the first case, a database of accounts of all network users is used, and in the second – a database where information about files on the server is stored.
The system of data management allows to achieve maximum storage efficiency and high availability of data, provides flexibility with respect to operating systems, and excellent performance in heterogeneous server environments and data storage systems. It technically easily realizes the storage and processing of information. This form allows you to create fairly simple technical devices for presenting (encoding) and recognizing (decrypting) information. For this reason, the binary system has become so widely used.
Which are the main types of data management frameworks?
Big data refers to information whose volume can be over a hundred terabytes and petabytes. Moreover, this information is regularly updated. Examples include data coming from contact centers, social media, data on stock exchange trading, etc. Also, the concept of “big data” sometimes includes methods and methods for processing them.
The main types of data management frameworks are the following:
- Strategy and Governance.
They bring data to a single format: they recognize text from photos, and convert documents, convert text into numbers.
If there are two sources of data about the same object, information from the first source is supplemented with data from the second to get a complete picture.
A well-defined, integrated, and comprehensive strategy enables and supports valuable data-driven decision-making across the organization.
Weed out redundant data: if some source collects unnecessary information that is not available for analysis, it is deleted.
Companies use the Big Data accumulated in their systems to improve operations, provide better customer service, create personalized marketing campaigns based on specific customer preferences, and ultimately increase profitability. Businesses that use big data have a potential competitive advantage over those that do not. They can make faster and more informed business decisions if they use data effectively.