Written by Ana Canteli on March 29, 2022
Data management is based on collection, custody, and efficient and safe use. Data management aims to help optimize its use based on data management policies and the regulatory framework. We must not forget that there are more and more companies whose core is data management. That is, they are not based on tangible material to create value.
Data management is said to have started around 1890 with the creation of punched cards. But in reality, until 1960, the concept of data management or data warehousing was not discussed as we use it today. The Association of Data Processing Services Organizations (ADPSO) began its advisory activity on master data management and data warehousing, among other issues. A decade later, the data management systems were only operational; they provided reports on operations at a given time - master data extracted from a relational database - data warehouse - stored in rows and columns.
Today, businesses need data management solutions that provide them with a unified way of managing data at multiple levels. Because data management tools are based on data management platforms and can include master databases, data lakes, data warehousing, big data management systems, data analysis, etc.
A data management platform is the primary system for collecting and providing large volumes of data analytics. Data platforms often include software tools for management and may be developed by the database provider or third parties. These data management solutions help technical teams and database administrators perform tasks such as:
As for big data, it is precisely what it sounds like: lots of data, lots of data. But big data comes in a wide variety of formats, and it's also collected at high speed. For example, think of all the data Meta collects from your social networks. The amount, variety, and velocity of that data make it so valuable to businesses, but it also makes it difficult to manage.
As more and more data is collected from sources as disparate as CCTV, social media, audio recordings, and Internet of Things (IoT) devices, big data management systems have emerged.
A data lake is a data storage system in its raw format, and it typically includes essential backups of the data from the source system.
Data is a form of capital, as in today's economy, it can create value for itself. Data are very relevant at a strategic and competitive level. Data is also a defined capital since it is information registered and necessary to produce goods or services. And as we said above, it includes any data captured:
Most of the challenges in data management today stem from the ever-accelerating pace of business and the increasing proliferation of data. The ever-increasing variety, speed, and volume of data available to companies push them to seek more effective management tools to sustain themselves. Some of the main challenges organizations face are:
A well-designed data governance program is essential in a solid and reliable data management strategy, especially in companies with distributed data environments that include many systems. A strong focus on data quality is also critical to applying best practices. However, in both cases, IT and data management teams can't do it all. Management, employees, and users must be committed to ensuring the proper use of data and maintaining data quality to apply best practices.
In addition, the multitude of databases and other data platforms available to implement requires careful data architecture design, and the appropriate technology must be evaluated and selected. Data managers and data management tools must ensure that the systems they implement fit their purpose and have the data processing capabilities and analytics information necessary for their organization's operations.
The OpenKM document management system has all the functionalities and capabilities to process an organization's data and configure or be part of the data management system that it develops. With OpenKM, your company will be able to get the most out of your data capital.
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