Data may be your most valuable resource. Data management refers to an organization's management of information and data for secure and structured access and storage. It is a process that includes acquiring, validating, storing, protecting, and processing required data to ensure the accessibility, reliability, and timeliness of the data for its users. Organizations and enterprises are making use of Big Data more than ever before to inform business decisions and gain deep insights into customer behavior, trends, and opportunities for creating extraordinary customer experiences.
But what makes data valuable? Its source? Its quantity? Its format? No, the value of data depends on what you do with it. And the first step in unlocking its potential lies in data management. So what do you know about data management? What do you need to know?
Data management tasks include the creation of data governance policies, analysis and architecture; database management system (DMS) integration; data security and data source identification, segregation and storage.
Data management encompasses a variety of different techniques that facilitate and ensure data control and flow from creation to processing, utilization and deletion. Data management is implemented through a cohesive infrastructure of technological resources and a governing framework that define the administrative processes used throughout the life cycle of data.
Data management solutions make processing, validation, and other essential functions simpler and less time-intensive. It is a huge area, and this really is just an over-arching term for an entire segment of IT.
Data Management Challenges
While some companies are good at collecting data, they are not managing it well enough to make sense of it. Simply collecting data is not enough; enterprises and organizations need to understand from the start that data management and data analytics only will be successful when they first put some thought into how they will gain value from their raw data. They can then move beyond raw data collection with efficient systems for processing, storing, and validating data, as well as effective analysis strategies.
Another challenge of data management occurs when companies categorize data and organize it without first considering the answers they hope to glean from the data. Each step of data collection and management must lead toward acquiring the right data and analyzing it in order to get the actionable intelligence necessary for making truly data-driven business decisions.
Data Management Best Practices
The best way to manage data, and eventually get the insights needed to make data-driven decisions, is to begin with a business question and acquire the data that is needed to answer that question. Companies must collect vast amounts of information from various sources and then utilize best practices while going through the process of storing and managing the data, cleaning and mining the data, and then analyzing and visualizing the data in order to inform their business decisions.
It's important to keep in mind that data management best practices result in better analytics. By correctly managing and preparing the data for analytics, companies optimize their Big Data.
Is your data easy to access, clean, integrate and store? Do you know which types of data are used by everyone in the organization? And do you have a system in place for analyzing data as it flows into the organization? Brush up on the concepts below to start your data management journey;
- Data access refers to your ability to get to and retrieve information wherever it is stored. Certain technologies can make this step as easy and efficient as possible so you can spend more time using the data - not just trying to find it.
- Data quality is the practice of making sure data is accurate and usable for its intended purpose. This starts from the moment data is accessed and continues through various integration points with other data - and even includes the point before it is published or reported.
- Data integration defines the steps for combining different types of data. Data integration tools help you design and automate the steps that do this work.
- Data federation is a special kind of virtual data integration that allows you to look at combined data from multiple sources without the need to move and store the combined view in a new location.
- Data governance is an ongoing set of rules and decisions for managing your organization's data to ensure that your data strategy is aligned with your business strategy.
- Master data management (MDM) defines, unifies and manages all of the data that is common and essential to all areas of an organization. This master data is typically managed from a single location or hub.
- Data streaming involves analyzing data as it moves by applying logic to the data, recognizing patterns in the data and filtering it for multiple uses as it flows into your organization.
Managing your data is the first step toward handling the large volume of data, both structured and unstructured, that floods businesses daily. It is only through data management best practices that organizations are able to harness the power of their data and gain the insights they need to make the data useful.