In a company, you must be familiar with the concept of management. Management is the concept of how to manage and organize something. There are various types of management concepts in a company, one of which is data management.
Data management is very important for companies because it provides various kinds of convenience for companies in processing incoming and outgoing data.
Data management covers various aspects such as processing incoming data, storing data, categorizing data, and deleting unnecessary or dangerous data.
Data management is very often found in various forms of digital data processing.
This helps companies from various industry sectors to realize effective administration and performance based on complete data.
Let's take a closer look at data management in this article. You will explore data management from the definition and concept of data management, to the challenges and objects of data management.
Definition of Data Management
Let's explore the definition first. What is data management? You must have come across this concept many times in your company either consciously or unconsciously.
In general, data management is a concept that includes the preparation and process of managing large amounts of data in various forms.
This preparation and process includes designing data management patterns, data categorization, and the execution process by a software that is tasked with managing the entire data.
As you know, this type of management process can usually be found digitally. So, almost all types of management exist in digital form.
Specifically, data management is an activity that concerns the use and security of organizational or company data.
Therefore, you need a specialized application for companies that is able to carry out this management concept effectively and in a planned manner.
Data Management Function
If you are thinking why should there be this management system in a company? Or why is data management important for the sustainability of the company in doing data processing?
Then there are some functions that can answer your question. Here are the general data management functions.
1. Increase Company Profit
By doing data management, companies can analyze the data available and stored in the company's data storage.
So that companies can provide data information that suits their needs and ultimately improve the quality of decision making that leads to increased company revenue.
2.Reduce Data Misinformation
Incomplete data can lead to misunderstandings and misinformation to consumers.
Companies that implement a good digital component management concept will reduce the percentage of data inconsistencies that harm both companies and customers.
3. Fulfill Company Regulations
Each company has its own regulations. This includes regulating the data management and security system.
This company regulation and data security will be achieved faster if the company uses an application system that fulfills all the concepts.
This is because any customer can legally sue if the company does not fulfill any of the regulations that have been set.
4. Data Management Object
Now that you know the functions of data management, you need to know what objects are the objectives of data management in a company or organization.
In this article, we have summarized some important objects that are the purpose of data management. Here is the explanation one by one.
5. Data Quality
Every data has a user experience that you should pay attention to. Such as the length of access, the ease of accessing it, and the security system for customers to receive and send data.
The company will make data quality one of the objects for which data management is carried out in several data sectors.
6. Data Distribution and Consistency
In addition to data quality, one of the objects of data management is the data distribution process and its consistency from customers to companies and vice versa, from companies to customers for certain needs.
A company that implements a good data distribution system to customers and is easy to understand will have higher credibility.
7. Big Data Management
For those of you who don't know what big data is, big data is data that is collected at a high speed in a short period of time.
An example of data management in this case is the management of a good video news feed that has high insight to customers.
8. Data Architecture and Modeling
A data must have a clear and organized composition and structure. This is for the convenience of communication between the company and customers.
Data management must take care of this object by grouping data according to the needs of the company to achieve targets effectively and on target.
9. Data Governance
We come to the most important object in this management, which is the data governance system. A data governance system is something complex that must provide convenience in access, delivery, storage, and clear data security.
This aims to benefit both the company and its clients. An example of data governance is a good data delivery system.
Data Management Challenges for Enterprises
Now that you know how content management objects and their groupings and applications.
You have to know what challenges you have to face when doing appropriate data management and giving your company an impact on the trust of each of its customers. Here are the challenges that must be faced.
1. Scale and Performance
One of the challenges of data management is that you have to scale and check the performance of both all employees and each division.
This process is time-consuming and complex to execute. This data management challenge requires you to coordinate with all the teams involved.
2. Requirements According to Customer and Company Needs
You also have to adjust the existing concept and data management system with the terms and conditions that apply based on agreements with customers and with your company regulations. So there must be regular and thorough checks.
3. Employee Training
A continuation of the previous data management challenge, this time you have to train the employees in charge to adapt to the agreed data processing system. So that there is no miscommunication between employees in the process of processing data to customers.
4. Optimization and Cloud Computing
Next you should perform optimization and customization cloud computing carefully and carefully. This must be done as a form of maintenance of existing data in the company.
Data Management Example
Here are some examples of data management implementation in the form of apps that you can use depending on your company's needs and management style.
DBMS (Data Management Systems)
One of its example is data management systems This example includes several applications that can perform digital data processing. Such as MySQL, Oracle, and SQL Server are used to store, manage, and call data.
Data Warehousing
Is an example where you can store various data in operated. Examples include Centralized data repositories for business analytics, such as Amazon Redshift and Google BigQuery.
Integration Data
This example combines data from various sources, for example ETL (Extract, Transform, Load) tools such as Talend and Informatica.
Data Governance
Proses mengelola ketersediaan, keandalan, dan keamanan data, seperti penggunaan kerangka kerja DAMA-DMBOK.
MDM (Master Data Management)
Mengelola data inti perusahaan, seperti produk dan pelanggan, dengan solusi seperti Informatica MDM.
Big Data Technologies
Mengelola dan menganalisis data dalam jumlah besar, contohnya seperti Hadoop dan Spark.
Data Quality Management
This example ensures that the data is accurate and complete so that the data stored is harmless and does not harm the company server.
You can implement it with data management applications such as Data Ladder and Trifacta.
Closing
This is the explanation of this article on data management. You already know about data management in detail starting from the definition of this management in general and specific, functions, to challenges and what you have to do to create a good and effective management system.
With data management, all company work related to data will be easier and provide greater profits for the company in the long run.
Some data management examples depend on several types and stages of data management. So you can consider what applications are suitable for your needs.
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