According to a 2020 data management statistics report, data quality problems cost American businesses more than $3trn every year. The same report highlights that the average business uses about 17 different applications to manage customer information. It estimates that although customer information doubles every two years, 99% of it is never analyzed or used.

Almost every decision that a business makes is driven by data, but it appears that the process isn’t very well understood.

To remedy this, businesses are keen to employ data experts. Whether you are looking to join the IT profession for the first time or are looking for a promotion, an online master’s in computer science from Baylor University will give you an edge. With the right credentials, you can secure six-figure employment helping companies develop data-driven strategies.

A master’s in computer science gives you an introduction to communication systems, software engineering, operating systems, algorithms and machine learning. It also teaches you about databases, data communications and different types of data management.

What is data management and what are the different types?

Data management is the collection, storage and use of data to drive decisions. Data management isn’t just for businesses. It is used by all sorts of institutions to drive strategy.

There are numerous examples of data management all around us. The government, for example, collects population information to know how to distribute resources across the US. Health organizations collect data on contagious diseases and use it to create emergency plans.

Businesses collect data because without it they would be flying blind. They wouldn’t know what products and services are in demand or where their customers are. They would have no idea about the sales cycle, the customer journey or customer demographics.

Data management types

There are several types of data management, and organizations and businesses blend them to come up with data management strategies that work for them.

  • Master data management

This type of data management, also called MDM, consolidates all information in a single version, and everyone in the business works off that version. Data collected from different sources is put in one location for everyone to use.

A good example of master data management is the customer database in a retail company. Salespeople collect customer information, which is entered into the database and updated as necessary. Everyone can refer to the database to get a snapshot of any customer.

  • Data stewardship

This type of data management is about developing policies and protocols for data and ensuring that they are followed. You can think of a steward as someone whose job it is to police how data is collected, analyzed and used. 

  • Data quality management

Data quality management is about policing the quality of information. It looks for duplications, errors, redundancies and other problems that may render it unusable.

In a customer database, for example, a quality manager checks to make sure customer addresses are correct, that they are not deceased and that there are no redundant email addresses.

Quality management is important because it removes data that would otherwise skew decisions.

  • Data security

Today, data security is the most important type of information management. Hacks have become commonplace, and millions of customer records are stolen every year.

This has led to huge investments in systems and protocols that secure customer information. Data security is implemented across every step of the data collection and storage processes.

Security professionals are also in charge of the data recovery process in case of a loss.

  • Data governance

This is the process of laying down laws that are used to manage data. Governors make policies, which guide other data managers on how to correctly collect and store customer details.

Professionals in this field often work with legal experts to develop frameworks on how to handle user information within the boundaries of the law.

  • Big data management

This is when businesses and organizations analyze data and use it to make decisions. Experts in this field create models or algorithms that are used to make sense of the information they have collected.

  • Data warehousing

All the data that businesses and organizations collect needs to be stored and managed using the right tools, and this is where warehousing comes in.

Many companies now rely on cloud servers to store their data. The warehousing department is in charge of making sure that it is safe at all times. They also ensure that it is available to authorized users.

Small businesses may not need to use all the different types of data management, but they will use one or two. Small online retailers, for example, rely on master data management to collect customer information. As they grow bigger, they may integrate quality management to make sure that customer information is correct and up to date.

Why is data management important?

Today’s businesses are information-driven. The ones that excel are the ones that know how to collect it, analyze it and use it to make strategic decisions. Data feeds algorithms, and algorithms rule the world.

Google is an excellent example of a business that understands the value of user information. It collects user data aggressively and uses it to drive ad placement. By looking at what sites a user visits, the company has a fair idea of their interests, and advertisements are placed based on those interests.

Retail businesses survive because of data. By analyzing the customer journey, they know who their demographic is and what products they prefer.

Companies that understand data collection and management systems are market leaders. They are willing to pay lots of money to attract talent that helps them stay at the top of their niches.

An online master’s in computer science teaches the requisite skills, and students are in a unique position to get IT jobs in some of the best companies in the US.

Conclusion

An online master’s in computer science equips students with valuable data management skills. They learn about information collection and handling, as well as how to store it safely. They are also introduced to policies that govern data use and learn how they can be used to drive business decisions.

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