What is Data Management and Why is it Important?

data management

What is data management?

Data management refers to the practice of managing the data by different processes such as storing, maintaining, protecting, organizing, and processing the data retrieved by an enterprise from various sources safely and securely with utmost efficiency. The main aim of data management is to reduce the risks related to data processing and provide accurate data to people and organization. Data management helps in better optimization of data and in turn, helps make better business-related decisions keeping in mind the rules, regulations, and policies of the business.

To manage the data in modern business, you need to implement various methods to benefit your organization. These methods are known as data strategies. A data strategy or a data management strategy is defined as the planning or strategy that is designed specifically to achieve long term business goals at a greater level. Nowadays Data strategy has become a significant part of organizations to create value out of their data.

To make sure that the data in organizations is accurate, available and accessible at all times, we require various data management process that consist of various functions. These tasks are majorly performed by the data management teams along with the IT department. However, the end-users or the business users also become a part of the entire process as the data is supposed to meet their demands as well to get them on board with policies making its use.

Management of data in the modern business in an enterprise consists of different kinds of tasks, processes, policies and practices. Therefore, there is a lot of scope in data management in terms of:

  • Data creation, updating and accessibility in a diversified environment.
  • Storing the data across various platforms.
  • Providing organizations with data availability and data recovery.
  • Making use of the data in the building of different types of web applications and algorithms.
  • Ensuring the privacy and security of data.
  • Archiving and destroying data keeping in mind the retention schedules and compliance requirements.

A proper data management strategy helps in tracking users’ activity and administrators. It also helps to find out whether data management technology is capable of fulfilling the needs and requirements of an organization, also if it is helpful in deriving data value.

For a smooth sailing of data management, we require data management platform which collects and analyzes large data sets across an organization or an enterprise. These platforms are the foundation where data is collected in huge volumes. Apart from this, there are commercial data platforms, which consists of different software tools for management. They are designed by the vendors of database or third-party vendors. These platforms help data management team or IT department consisting of data engineers in performing various tasks like:

  • Finding out faults, bugs, or errors in the database system or to look for any system alerts and resolve them immediately.
  • Database memory allocation and storing of resources.
  • Modifying the design of the database and optimizing results for better performance of the applications.

The cloud data platforms are becoming extremely popular these days as they allow organizations to move upwards or downwards in a manner which is fast and cost-effective. Some of these platforms are even available as a service, to help save business more money.

master data management

Types of Data Management

Data management is of various types:

1. Master Data Management

To make sure that the organization is working on the correct, accurate and truest information we require master data management. It helps in reducing the unnecessary data processing. And the techniques in master data management collects data from diverse sources and display it as one fixed and reliable source. The tools in MDM come in handy to make any reforms in the data.

2. Data steward

A data steward is responsible for management policies regulations. They must keep a check on data collection, make sure if correct practices are being implemented and executed abiding rules while performing organizational tasks.

3. Data quality management

Data quality management is responsible for finding out any hidden or underlying data management  mistakes or errors and any discrepancies in the collected data. Data quality managers are required to perform these tasks on a regular basis.

4. Data security

data security is the most integral part of data management. It is the utmost key step in data management and implementing DevSecOps helps to maintain data security by ensuring that there are security checks at every level be it the developmental phase or during the exchange of information. Data security specialists are required to do encryption management. Their job is to prevent any unauthorized access and look for any accidental movement or deletion or other forthcoming obstacles.

5. Data governance

As the name suggests, data governance is referred to the governing of data inside an organization. Data governance is responsible for setting the precedents and laws for the state of information in an organization. A data governance framework is similar as that of a constitution as it also helps in implementing the policies, rules, and regulations for the data related processes. Data governance is responsible for protecting the data and it overlooks the above-mentioned areas such as data stewards, data quality management, data security as well.

6. Big data management

Big data has become widely popular nowadays as it helps in the data management of raw rata. Big data in simpler terms means data in substantial amounts, the collection and analysis of large data sets is referred to as big data management and is done using tools of big data in modern businesses.

7. Data warehousing

It is the process of collection enormous amounts of information by an enterprise. A data warehouse consists of more than one database and inside each database there are rows and columns in the form of tables. Data warehouse management is a process in which the raw data is analyzed in depth to derive various insights about business as well as to supervise the cloud-based infrastructure to accumulate raw data.

Importance of data management

In today’s date, data is the most powerful asset any business or organization can have. Data helps make sounder business-related decisions, product enhancement, marketing campaigns, building better customer relationships etc., while cutting down the overall costs all to gain profits. But to achieve all these goals, an organization requires a proper data management strategy and a lack of one can hinder the organization’s growth.

The importance of data management has grown vastly as organizations are getting more regulated in terms of data security, data privacy and laws (I.e., GDPR and the California Consumer Privacy Act) have also come into the picture. Apart from this, companies’ data consumption has swollen immensely with the increasing number of data types and database systems in big data. If one is not equipped with good data management, it becomes tough to achieve long term goals and generate revenue. Some of the most significant reasons why data management is important are:

1. Improves decision making

In today’s date, data is the most powerful asset any business or organization can have. Data management helps make sounder business-related decisions, product enhancement, marketing campaigns, building better customer relationships etc.

2. Reduction in loss of data

If there is a secure gateway to the data to be accessed, it will ultimately reduce the risks of data leaks or any kind of data loss. Relying on safe and trusted sources helps in reduction of data loss.

3. Better data security

In the age of social media where all our personal and confidential data is out there, mindful data management practices help in keeping the confidentiality of such personal data for e.g., contact numbers, addresses, bank account details etc.

4. Lesser costs

If organizations follow data management strategies from the start itself there will be lesser chances of expenditure on resolving poor management issues and they can save a fortune as well as succeed in a smooth functioning of the business.

5. Increased efficiency and productivity

If all the above practices are followed diligently and the data available is accurate and reliable, this will eventually result in increased efficiency and productivity of the employs in the organization. As they can perform their tasks in lesser time yielding more productivity.

Data Management Skills

Data Management Skills

Data management processes require certain set of skills to successfully implement the data strategies as well as achieve high-level goals. They are:

  • Data Analysis: Effective and efficient use of data to improve operations and develop programs as well as reporting, summarizing lists, searching for different patterns, and analyzing outcomes requires knowledge of data analysis tools and techniques in order to fulfill the needs of your clients and customers and create value out of that data.
  • Database Software navigation: If you are working in a data management team, it is expected of you to have sound knowledge of database software and how to use them in order to find records, sort, review, edit, print, and other functions. One should know how to access the built-in forms and reports in the database. There are distinct functions in the software that are to be learned and explored along with creating reports with the help of existing tools, writing queries and rewriting data into Excel or other formats for further analysis.
  • Data Integrity: To understand different definitions, guidelines of programs and sources of data. Creating transparent communication channels, review of data and ensuring that data that is worked upon is accurate and true in nature. Be alert while analyzing data and look for any potential weaknesses in the data.
  • Management of Accounts and Files: In order to keep track of the online accounts and helping people with the credentials of their accounts, managing accounts is important. Major tasks include organization of files and folders on the system or network. Copying, pasting, uploading, moving or download files and photos, and using email to send across various attachments is also a part of the job.
  • Designing and Planning of database: To design the database according to “relational database design” concepts (table structure; one-to-many relationships). To be aware of the merits and demerits of different database types and to be able to take part in short and long term planning of database projects and to collect and analyze data effectively and efficiently.

Advantages of Data Management

Data management helps organizations in numerous ways by identifying and resolving underlying errors and help provide a better customer experience altogether.

For starters, data management gives organization insights about how to measure that truckloads of data that they have. Data management helps business managers look at the larger picture in order to gain perspective and have a better approach towards growth and planning.

As soon as the data management strategy is in place, data can then be used to dig gold in terms of business: business intelligence. Digging for useful information can help enterprises in a lot of ways such as:

  • Advertisements that target audiences with respect to their inclinations and interests.
  • All-encompassing security that shields crucial data.
  • Arrangement with important consistence norms, setting aside time and money.
  • AI (Artificial Intelligence) that becomes all the more ecologically mindful after a period, fueling programmed and consistent improvement.
  • Decreased working costs through usage of just the vital stockpiling and figure out power needed for ideal execution.
  • Shoppers and purchasers gain profit by data management as well. By observing their interests, inclinations and shopping propensities, organizations can offer clients quicker admittance to data they need. Prospective buyers admire customizations in their shopping feed and find it convenient to pay online with full safety of their confidential data.

Data Management Challenges

Major challenges in data management are:

  • Suppose there are no defined data management processes. In that case, organizations may find siloed data, and it becomes a challenge to find and access true and relevant forms of data that too when the data is scattered all over the place. To extract data from a trusted and safe source is the real task.
  • To transform unfiltered and unstructured data into a structured one is the real deal. When collected initially, data is usually scattered and unstructured. To create value out of that data, the organizations need to mine through the data and analyze it for it to become of any use. Third-party organizations often help businesses in these processes.
  • Management of people in the organization is also as integral as data management to grow and prosper. The employs must also know the advantages of using data management practices and how it will help them personally and professionally. Some of these are the challenges that businesses face in their day-to-day cycles, but they can be easily avoided with efficient data management practices and strategies and upcoming technology combined.

Wrap Up

Data management comprises of various processes such as storing, maintaining, protecting, organizing, and processing the data retrieved by an enterprise from various sources safely and securely with utmost efficiency. Several types of data management include Master Data Management, Data Steward, Data Security, Data Governance, Data Quality Management, Big Data Management and Data Warehousing. Data is important to make better business-related decisions, aid in product enhancement, marketing campaigns, building better customer relationships etc.

To execute these practices, skills like data analysis, data integrity, database software navigation, accounts and files managing, and designing and planning databases are required. Data management comes with its own advantages and disadvantages, but if correct data management techniques are implemented, a business can reach greater heights and achieve all the long-term goals.

Frequently Asked Question

What are the three main goals of data lifecycle management (DLM)?

Availability, confidentiality, and integrity are the three main goals of data lifecycle management or DLM.

Why is data important?

Data is the key to make sound business decisions, finding new and potential customers, running smooth operations at an organization.

What is the first step in effectively managing data for a firm?

Ideally, the first step should be to conduct an audit and prepare an audit report in order to manage the data of a firm effectively thereafter.

What does a data manager do?

A data manager oversees the analyzing of huge datasets and is responsible for developing various systems to run an organization successfully.

WRITTEN BY

Himanshu Mishra

Technology Head
Himanshu is an entrepreneur with 17+ years of overall experience in strategic and advisory roles in Senior Management, IT program management, Quality Assurance, and ERP implementations. He has invested in companies focused on Digital Technologies and Healthcare industries. He has previously worked in domains like: Technology, Finance, Marketing… Read more

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