Modernize Your Way of Data Management to be Competitive in '24
Companies are keen to use new ideas and technology to obtain a competitive advantage. The biggest problem for companies, though, is being bombarded with excessive information and catching up fast transitions. Being an adaptive competitor in a rapidly changing business environment involves more than just utilizing new technologies since technologies are often ineffective in the absence of high-quality data.
Around the world, 2.5 quintillion bytes of data is generated every day. For most companies, dealing with massive amounts of data, including structured and unstructured data, is difficult. It might be challenging to extract timely insights from many types of data. In order to use data at a scale, companies should have a modern data storage system.
What is data modernization?
Data Modernization is the process of moving data from an outdated database to a more modern/dynamic database that fits the needs of business. Data modernization matters due to following reasons:
1. Increase Returns on your digital investments
One of the most important ways to gain a competitive edge is the capacity to adapt to changes in today’s rapidly changing business environment. Organizations are eager to transform their processes. However, a lack of organizational agility leads to fewer returns than expected.
To gain a competitive advantage, keeping up and integrating new approaches/technologies into your business processes is not enough. You need to modernize your data storage and move your company’s data to a modern platform.
2. Enables to become a truly data-driven company
Companies generate massive amounts of data from a wide variety of sources in multiple formats. Data enables companies to understand who interacts with their products, on what kind of occasions and places. Nevertheless, processing, storing, and analyzing vast amounts of data in different formats is difficult.
With technological improvements such as IoT and sensors, the nature of data has changed. These innovations produce stream data. Thus, data is continually and in real-time evaluated. With traditional databases, it is challenging to process and analyze enormous amounts of streaming data instantaneously.
Companies can analyze enormous amounts of all data types, including structured and unstructured data – video, audio, and image – in real-time with modernized data architecture.
3. Improve data governance and privacy
Data governance provides information about what data companies have, who owns or manages the data, data source, etc. Therefore, data governance is crucial for data modernization projects, and an effective data governance strategy will unlock the efficiency of your company’s data.
Data modernization prevents unauthorized disclosure by monitoring data usage. To provide transparency over the life cycle of data, it uses the data lineage technique. Companies can see how datasets are used and what changes have been made. It also provides details about how the data has been sourced and stored within a migration project.
Strategic roadmap for data modernization with advice and outcomes
Path 1: Evaluate your current legacy database and know your scope
- Decide which departments or cases are prior to the data modernization initiative.
- To provide more flexible access to massive volumes of data, obtain extensive information about the existing data, such as what data is used, where it is sourced, and who uses this data.
Recommendation: To better decide the next steps in data modernization, comprehensively understand your data volume, data source, and data types.
The bottom line: Determining scope will enable companies to focus their modernization data effort on a certain department or case. Defining the scope of data modernization projects prevents running over budget and time.
Path 2: Create a migration planning and ensure data security
- Modernization data processes must align with your company’s information management strategy.
- Establish a realistic timeline for the data modernization process. It is critical for resource planning activities
- In order to avoid data loss ensure there are previous versions of your data.
Making a data backup and testing all data modernization steps prevent potential data leakages. Educating and training employees also plays an important role in data loss prevention.
The bottom line: Data loss can damage companies’ productivity, reputation, and revenue. A data loss prevention strategy reduces the data loss risk and prevents the potential cost of data breach.
Path 3: Test and validate modernized data
After moving legacy data to modern storage, test and validate new data storage to ensure that all data has been migrated to the target platform successfully.
- Make sure that only the appropriate people will have access to and permission to modify your business data. To ensure it you can adapt a zero trust cybersecurity approach.
- Monitor the new data environment to make sure availability and usability of data for its desired purpose.
The bottom line: You can determine whether the new modern database is efficient and meets the needs of your company.
- Data anonymization: Overview, Pros, Cons & Techniques
- Data Parsing to Extract Meaningful Information From Data Sources
For guidance to choose the right tool, check out our data-driven lists of vendors prepared for different solution areas :
If you believe your business can benefit from data modernization, but still have some doubts how to choose the right tool, reach out to us:
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