A Definition of Data Management
Data management is an administrative process that includes acquiring, validating, storing, protecting, and processing required data to ensure the accessibility, reliability, and timeliness of the data for its users. Organizations and enterprises are making use of Big Data more than ever before to inform business decisions and gain deep insights into customer behavior, trends, and opportunities for creating extraordinary customer experiences.
To make sense of the vast quantities of data that enterprises are gathering, analyzing, and storing today, companies turn to data management solutions and platforms. Data management solutions make processing, validation, and other essential functions simpler and less time-intensive.
Leading data management platforms allow enterprises to leverage Big Data from all data sources, in real-time, to allow for more effective engagement with customers, and for increased customer lifetime value (CLV). Data management software is essential, as we are creating and consuming data at unprecedented rates. Top data management platforms give enterprises and organizations a 360-degree view of their customers and the complete visibility needed to gain deep, critical insights into consumer behavior that give brands a competitive edge.
Data Management Challenges
While some companies are good at collecting data, they are not managing it well enough to make sense of it. Simply collecting data is not enough; enterprises and organizations need to understand from the start that data management and data Analytics only will be successful when they first put some thought into how they will gain value from their raw data. They can then move beyond raw data collection with efficient systems for processing, storing, and validating data, as well as effective analysis strategies.
Another challenge of data management occurs when companies categorize data and organize it without first considering the answers they hope to glean from the data. Each step of data collection and management must lead toward acquiring the right data and analyzing it in order to get the actionable intelligence necessary for making truly data-driven business decisions.
Data Management Best Practices
The best way to manage data, and eventually get the insights needed to make data-driven decisions, is to begin with a business question and acquire the data that is needed to answer that question. Companies must collect vast amounts of information from various sources and then utilize best practices while going through the process of storing and managing the data, cleaning and mining the data, and then analyzing and visualizing the data in order to inform their business decisions.
It’s important to keep in mind that data management best practices result in better analytics. By correctly managing and preparing the data for analytics, companies optimize their Big Data. A few data management best practices organizations and enterprises should strive to achieve include:
- Simplify access to traditional and emerging data
- Scrub data to infuse quality into existing business processes
- Shape data using flexible manipulation techniques
It is with the help of data management platforms that organizations have the ability to gather, sort, and house their information and then repackage it in visualized ways that are useful to marketers. Top performing data management platforms are capable of managing all of the data from all data sources in a central location, giving marketers and executives the most accurate business and customer information available.
Benefits of Data Management and Data Management Platforms
Managing your data is the first step toward handling the large volume of data, both structured and unstructured, that floods businesses daily. It is only through data management best practices that organizations are able to harness the power of their data and gain the insights they need to make the data useful.
In fact, data management via leading data management platforms enables organizations and enterprises to use data analytics in beneficial ways, such as:
- Personalizing the customer experience
- Adding value to customer interactions
- Identifying the root causes of marketing failures and business issues in real- time
- Reaping the revenues associated with data-driven marketing
- Improving customer engagement
- Increasing customer loyalty