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SmartData Collective > Data Management > Steps Companies Should Take to Come Up Data Management Processes
Data ManagementExclusive

Steps Companies Should Take to Come Up Data Management Processes

Companies need sound data management strategies to make the most of their digital business models.

Dariia Herasymova
Dariia Herasymova
8 Min Read
tips for companies coming up with data management strategies
Shutterstock Photo License - NicoElNino
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Data is becoming more important to modern organizations than ever before. However, many companies are still struggling to use it effectively. One poll found that 74% of companies feel they are still struggling to use data effectively.

Contents
How Companies Can Manage their Data BetterData management involves a few main components:Data management is a set of skills that you can learn and develop. These include:

One of the problems is that they don’t manage their data well.

How Companies Can Manage their Data Better

The process of managing data can be quite daunting and complicated. Data management is a set of processes and policies that organizations use to collect, store and share data. It involves understanding how the organization uses data and how the data is stored, and then working out what to do with it.

The main objective of data management is to collect, collate, analyze, store, manage, update, and use data for decision-making. Data Management is considered to be a core function of any organization. Data management software helps in reducing the cost of maintaining the data by helping in the management and maintenance of the data stored in the database.

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Data management systems provide a systematic approach to information storage and retrieval and help in streamlining the process of data collection, analysis, reporting, and dissemination. It also helps in providing visibility to data and thus enables the users to make informed decisions. Data management software helps in the creation of reports and presentations by automating the process of data collection, data extraction, data cleansing, and data analysis. It also helps in the analysis of the data using sophisticated statistical tools and then producing reports and presentations for the decision-makers.

Data management software is useful in collecting, organizing, analyzing, managing, disseminating, and distributing information. The main objective of TDM is to facilitate the process of data collection, analysis, and decision-making. It helps in providing visibility to the data stored in the database and thus enables the user to make informed decisions.

There are various types of data management systems available. They vary in terms of their complexity and application. These include, but are not limited to, database management systems, data mining software, decision support systems, knowledge management systems, data warehousing, and enterprise data warehouses. Some data management strategies are in-house and others are outsourced.

Data management involves a few main components:

Databases: are used to store and retrieve data. They are a part of the data management system. A database consists of data structures or data models which are used to store and organize information. Data models help in storing and retrieving the data efficiently.

Data mining: is the process of discovering patterns in the data by applying different techniques such as data classification, clustering, regression, association, time series prediction, etc. These techniques are applied to identify hidden relationships and patterns in the data. Data mining software is used to discover the patterns in the data.

Decision Support Systems (DSS): help in making decisions by analyzing and synthesizing information. It is basically a process of developing and maintaining information systems, which are designed to assist the decision-makers by analyzing and synthesizing information. These systems are used to solve problems, make recommendations, suggest alternatives and help the decision-makers in making informed decisions. Decision support systems can be implemented at the tactical level, the operational level, or the strategic level.

Knowledge management: is the process of collecting, organizing, sharing, and managing knowledge. Knowledge management software is the tool used to manage and share knowledge.

Enterprise Data Warehouses: is used to consolidate the data from multiple sources into a central repository. This is done so that it becomes easier to find and access information in one place. Enterprise Data Warehouse is a tool that helps in analyzing the data and provides visibility to the information stored in the database.

Data collection: This is the gathering of information from a variety of sources. For example, we might collect data about our customers (such as their contact details), their likes and dislikes, their purchasing patterns, their preferences, and feedback. In the case of schools, we would need to gather information about their enrolment rates, their curriculum requirements, and how their students perform.

Data storage: We store this data in a computer, which is usually managed by a data manager. They need to ensure that the information is secure and available to those who need it. For example, we might store the data about the customer in a database.

Data analysis: Once we have collected the data, we analyze it using statistical methods, such as modeling, to see how it might be used to support decisions. In education, data analysis could involve analyzing student records to see if students are achieving.

To support data management, you need the right skills and knowledge. It requires a different mindset from the ones needed to simply manage records. In education, data management is about working with data and using it to support decision-making. This involves:

• Understanding what data means to your organization

• Having the skills to understand how the data is structured, what it says, and what it tells you

• Being able to collect and analyze the data

• Knowing how to access and use the data

• Having the right policies, procedures, and tools to support data management

It is important that you know what you are doing. The more you understand about the data you are managing, the better you will be at supporting your organization. To help you, you can look at the Data Management Checklist. This provides questions to ask yourself about the data you are managing. It may also help you to identify what additional training you might need to develop your skills.

You will also need to find out what data is needed, who needs it, where it is, and how the data will be used. This requires you to think about the context of the data, and your organization’s business strategy, as well as the data itself. It will help to understand your organization’s structure and the context in which data will be used.

Data management is a set of skills that you can learn and develop. These include:

  • Learning the basics of data
  • Working out the purpose and meaning of the data you collect
  • Understanding the difference between data and information
  • Understanding the purpose of data management
  • Understanding what your organization needs to achieve its goals
  • Recognizing when you have a problem
  • Knowing what to do
  • Being aware of relevant legislation
  • Being able to work with the team
  • Developing your communication skills
  • Knowing how to work with IT
  • Getting help when you need it
  • Having a clear set of policies, procedures, and practices

TAGGED:data in businessdata management
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ByDariia Herasymova
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Dariia Herasymova is a Recruitment Team Lead at Devox Software. She hires software development teams for startups, small businesses, and enterprises. She carries out a full cycle of recruitment; creates job descriptions based on talks with clients, searches and interviews candidates, and onboards the newcomers. Dariia knows how to build HR and recruitment processes from scratch. She strives to find a person with appropriate technical and soft skills who will share the company's values. When she has free time, she writes articles on various outsourcing models for our blog.

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