Along with technological advancements, we cannot deny that digital transformation is something that companies must implement. Because otherwise, the company will actually face delays and even delays in business growth (business growth).
One form of transformation that companies must implement is in terms of data processing or data management. Data processing is an important aspect of all business processes. Since data is the main element that needs to be organized, mapped in a structured way so that companies can easily process it (cleanse and process data).
Especially large amounts of data (big data) stored in company databases. The easier it is to access data, the smoother the business process will be. It is included in the company’s decision-making process that focuses on data analysis as a source of information. So, what is data management and how does it apply to business?
What is big data management?
Big data management is the process of ensuring whether data can be easily and timely accessed. This data processing includes data validation, data storage, data processing to data repair.
Of course, considering that now almost all companies have used big data for their business, data processing is very important. Especially companies involved in technology and SAAS. Such a large volume of data cannot be analyzed using traditional methods.
If companies use it well, big data makes analysis and business decisions easier. Because from this data analysis, companies will be able to make business predictions (business forecasts) in the future.
Starting from sales forecasting, financial forecasting, to being useful in the SDLC process and product development. In addition, analyzing the results of this data processing can also be useful for finding the right business strategy and marketing strategy in the future.
Starting with understanding customer behavior (consumer behavior), customer sentiment, improving user experience and customer experience, market orientation, helping to gather insights and more.
The important role of data management in business
Based on the above explanation, of course we know how big is the role of data management in business processes. Even to quote Tech Target, alongside the development of technology, data has become one of the most valuable business assets.
Customer data, employee data, product data, competitor data and company data. Because with data, companies can make business decisions based on valid information, create more effective marketing campaign strategies, and optimize time and costs.
These benefits are definitely the reason why data management is something that companies should implement.
Because without accurate data processing, the information that the company obtains can be invalid and actually cause many problems in the future. In fact, the company may experience a decline in sales growth, fail to make a profit, and experience the risk of a total loss (net risk).
Big data management system
After knowing the definition and important role of data management for business, now you should also know about different data processing systems. Starting with Oracle, here are data processing techniques that companies often use and are quite effective:
1. Database Management System (DBMS)
The first is a DBMS or database management system, specifically a relational DBMS. The system can organize data into rows and columns that contain all the records in the database. DBMS is very suitable for processing large amount of data. The system also supports machine learning. Aside from relational DBMS, there are many options that companies can consider. Also Read: Understanding Data Analysts and Their Role in Business Understanding the Difference Between Data Science and Data and Process Analytics
2. Big data management
The next system is big data management. As the name suggests, the main focus of this system is the efficient and secure storage and processing of large amounts of data. All these processes will be done in data warehouse. The data warehouse itself is a method based on relational and columnar databases. which displays the data of different operating systems but structured and ready for analysis. Typically, this data will be very useful for predictive modeling, machine learning, deep learning, and other analytical applications.
3. Data integration
Data integration is the next stage of data integration, which is the process of receiving different types of data. Starting from the process of data wrangling (collecting to sorting raw data), processing data to managing data so that it can be easily accessed.
4. Data analysis
The last one is data analysis. The purpose of this analysis is to find insight or insight into the processed data.
For example, for descriptive, prescriptive, predictive analytics. There are various methods that companies can use in data analysis. Typically, this process uses data analytics, machine learning, and data visualization, such as AI (artificial intelligence) visualization. These are the things you need to know about data management and its important role for companies.
From the above explanation, we can conclude that data management is a process that companies should implement. Not only can it simplify overall business process management, but it can also help companies gain new insights.
Because basically, effective data management can help companies make the right decisions. Meanwhile, you can also use the services of a digital marketing agency to help develop your business.
Some of the marketing strategies that can be implemented are growth hacking marketing, inbound marketing, 360 digital marketing and data driven marketing so that the company can grow quickly.