Everything You Need to Know
Data Management is an integral part of every business. Whether you’re dealing with customer or employee information, research data, internal records, or performance metrics, data must be properly managed.
This keeps your organization’s information organized, secured, accurate, and readily accessible to the people who need it, when they need it. This allows people and organizations to use data for decision-making, turning it into an asset for the organization.
What is Data Management?
Quite simple, managing an organization’s information and data. It involves creating policies and procedures which allow an organization to collect, organize, maintain, and secure data so that it can be accessed and used in a cost-efficient manner. In an increasingly virtual and data-driven world, analytics are more important than ever. As such, the ability to collect and manage data is an asset for all kinds of businesses and organizations. Without a system in place for data management, it would be impossible to produce reliable analytics. The result of this would be missed opportunities or inaccurate information that could potentially be used in important decisions or actions on behalf of the organization.
Components, all of which must be accounted for and managed in a way that keeps information organized, secure, and accessible. All these elements must be considered and included in a quality data management plan. If certain elements are left out of the data management plan the result would be a real, tangible impact on the organization’s ability to manage data at all.
According to DAMA International, the Global Data Management Community, there are eleven different knowledge areas that make up data management. Those knowledge areas include:
- Data governance: This includes planning and managing the data that the organization will use.
- Data architecture: This is the organization’s data structure and how it interacts with the rest of the organization.
- Data modeling and design: This element has to do with analytics and the systems that will perform them.
- Data storage and operations: This deals with the system’s physical hardware that will be used as part of the data management system.
- Data security: This element has to do with security data and managing who has access to information.
- Data integration and interoperability: This has to do with organizing and maintaining data in a database or other format.
- Documents and content: This deals with unstructured data and integrating information with databases.
- Reference and master data: These are the systems and processes that eliminate repetition and mistakes in the data by using standardized metrics.
- Data warehousing and business intelligence: This includes using data for making business decisions and other analytics.
- Metadata: This involves managing data that references other data.
- Data quality: This element includes data monitoring, source monitoring, and quality assurance through removing unreliable or other poor-quality data.
Big Data Management
Data management is essential for a big data model. If you or your organization is interested in big data and analytics, it’s important to understand that you can’t have one without the other. Data management deals with data from start to finish – from the moment that it comes into existence until it’s no longer
Tools and Strategies
When it comes to data management, both human professionals and software tools are valuable to an effective strategy. Organizations must have both data management professionals or a data management team that have the skills and knowledge necessary to create and maintain effective data management systems.
Data Management Professionals
An organization’s management team should employ professionals that are trained and skilled in several basic proficiencies. For starters, a professional should have a solid
computer science background and be able to use general computer science skills to organize data. Data management involves a good amount of database programming skills. A data management professional should be able to work with a database platform using its respective database language, whether it’s SQL, XML, Python, PERL, or others. These individuals should also be familiar with cloud computing and be able to use platforms like AWS, Microsoft Azure, Google Cloud, IBM Cloud, or others to manage, organize, and analyze the organization’s data. Business intelligence and business analytics are essential elements of data collection and use. Understanding how and why the organization uses analytics is important for any data management professional.
In addition to professionals in the field, organizations can also use data management software to collect, organize, secure, and use data. There are many different tools and platforms available,
so it’s important to understand what each of them does well and how it would fit into your organization.
Some of the most popular platforms include:
- Salesforce Audience Studio
- Google Cloud’s software
To implement a strategy in your organization, you should approach it like any other upgrade or improvement to the business. Start with your goal – what do you hope to do with the data
you’re organizing? Understanding the desired result will help guide your strategy and the steps you need to take. After you have a goal in mind, you’ll be able to lay out the steps you need to take to make it a reality. Depending on what state your data is in presently, you may need to start with organizing the information, moving it around, or performing various analytics. Depending on your needs, you may need to hire or train employees, obtain data management software, or create a plan with a timeline for completing the project. Start by building a data management team to work on the project and move on from there.
Once you have the personnel and tools in place, the management team should be able to carry out the necessary tasks to get your data organized and accessible. Then, you’ll be able to use the data
productively to make decisions and take value-added actions that are data-based. Don’t get discouraged if the process takes some time. Data management doesn’t happen overnight. Just remember that an efficient and effective data management system is the groundwork for valuable use of the data that you already have available to you.