What is data mapping and why businesses need data mapping? It’s the 21st century, knowing what a data map is and how it can influence the growth of your business is vital. For example, marketing in business has gone beyond the casual publishing of ads in newspapers or creating mini-concerts on Broadway Street. In the same vein, data has risen to become an integral part of every decision being made in business; product, sales, technologies, customer success, etc.
Also, due to the ease with which companies can collect insight these days, data manipulation and management have become incredibly complex. For data processes to be successful, data mapping is essential. Hence, as a business executive or budding data enthusiast, it’s important to understand the basics of a data map.
What is data mapping?
In simple terms, data mapping involves matching fields from one database to another. Data mapping is a core step for further data migration, integration, enrichment, etc. Being the core of several other data processes, precision is essential in data mapping. A misstep in the process can lead to a flurry of data inaccuracies across your organization.
The world has, for companies especially, become a global village. Different platforms connect the world. Also, because having insight and data is important in helping businesses know what their customers need, executives are leveraging the different connectivity platforms in sourcing data. Other sources like forms, analytics, etc., are also used in collecting data. Owing to this, businesses move data across systems frequently.
However, because platforms are different, data storage also differs. So, different systems can store the same data in different ways. Hence, it’s important to create a roadmap for data to get moving across these different systems. Data map allows data to reach its destination accurately.
How mapped data is at the final destination reflects its quality. The higher the quality of data, the more your business can rely on it through other processes and more decision-making.
For example, you can map a person’s name from one database to their phone numbers, address and even email in another database. Data mapping has a couple of phases to it. However, when done right, data mapping has tremendous benefits for a business.
WHY BUSINESSES NEED DATA MAPPING
Data mapping is not the easiest business process to execute. However, when done with precision, it has the following benefits for your business.
Organization of Data
Businesses collect data from several sources. What data mapping is helps makes the bulk of data less bulky to analyze. Thanks to data mapping, it becomes easier to track data without getting confused. When data is well organized, it becomes easier to make sense of insights therein.
Transparency for Analysts
Working on data will require different professionals at different times. Employees of an organization change. Hence, when the data map is efficient, it becomes easier for a new data analysis professional to pick up the role and make sense of the data.
Data mapping also aids the quality of the database, helping your company’s analyst make accurate decisions on the spot. Mapped data shows real-time sources and destination information, giving structure to the use of data in your company. Understanding the flow of data is vital; mapping allows that.
Optimized for Efficiency during Complex Process
The analysis of data is bound to get complex with time. So much data is available these days, it’s becoming difficult to manage it effectively. A good data map makes the transformation process easier. In addition, when data get complex, an efficient map saves time and reduces error potentiality.
THE DATA MAPPING PROCESS
- Define: The definition of the data to get moving begins the mapping process. The definition process involves the tables and fields within each table. Also, the format of the field is important.
- Mapping: This involves matching the source fields with destination fields
- Transformation: A transformation formula is coded if needed
- Test: A test system and sample data runs to see if the mapping works
- Deployment: Once the data transformation works to plan, the migration can go live
- Maintenance and update: the data map requires frequent updates and maintenance checks
THE DATA MAPPING TECHNIQUES
Manual Data Mapping
As the name implies, this process requires lots of work. Manual data mapping involves adequate data connection and process documentation. The languages commonly used in this case are C++, Java or SQL. The movement of data between databases is facilitated by techniques like; Extract, Transform and Load functions. Manual data mapping is easily customizable; hence, flexible.
Semi-Automated Data Mapping
The semi-automated techniques leverage graphical representations of data links to map data. This technique requires coding knowledge, which helps achieve flexibility and effectiveness. In addition, the technique can lead to the generation of a visual data interface.
Automated Data Mapping
The automated data mapping technology makes it possible to execute the process without coding. Requiring no technical knowledge, automated data mapping carries out processes like; sorting data, refreshing analysis, scheduling change captures, etc. On the downside, however, automated data mapping is tool-specific.
Hope now you know, what is data mapping. Managing complex databases can be a nightmare without proper measures in place. Accurately done data map makes it easier to make a decision, which ultimately contributes to the sales and revenue growth of the company.
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