You don’t want to waste time simply guessing what a potential client or client wants and needs from your company, or how they will react to a particular marketing campaign or strategy that you want to implement.
Instead, you can turn to the process of data-driven marketing to make informed decisions based on real data to ensure that your marketing efforts are relevant to prospects and customers’ interests and behaviors.
Now you may be thinking about the fact that your company has a large amount of complex data spread across multiple sources – this is where data mapping comes in handy.
Data mapping
Data mapping is an important part of data management and data integration. That’s because you take a close look at and consider all of your data – in other words, data mapping allows you to integrate your data from multiple sources.
In this blog post, we’re going to talk more about what data mapping is, why it’s useful, data mapping techniques, and data mapping tools.
What is data mapping?
Data mapping is the process of matching data fields or elements from one or more sources with their associated data fields in another destination – this is how you create relationships between data models located in different sources or systems. Data mapping software and tools automatically match data fields from one data source to another for you.
With data mapping, you can organize, distill, analyze, and understand huge amounts of data stored in various places so that you can draw conclusions and insights.
Why is data mapping useful?
Here are a few more reasons data mapping is both useful and necessary:
- Integrate, transform and migrate data and easily build data warehouses.
- Create direct relationships between your data from multiple sources at the same time.
- Make sure your data is of high quality and accuracy (data mapping software can automatically detect inconsistencies and data that is not of high quality or accuracy).
- Identify real-time trends and easily and efficiently share data reports with team members.
- Make sure you get the most out of your data and apply insights and insights appropriately.
- Use data mapping software to simplify the process of code-free data mapping (and automate much of it).
Examples of data mapping
A company like Amazon may use data mapping to target you. They do this by drawing insights from your browsing habits, reviews, your purchase history, and your time on the page. You can then retrieve this data and combine it with data from other sources such as demographic information.
By combining these types of data sources, Amazon has the information it needs to target you with specific products and personalize your shopping experience in different ways (e.g., age, and more).
Let’s consider another example of data mapping: suppose you work for a television network and you want to organize television shows on the network, actors appearing on the network, and actors within a show appearing on the network. The data exchange between the three sources can look something like this:
Data mapping techniques
There are three main techniques used in data mapping: manual mapping, semi-automatic mapping, and automated mapping. Let’s talk about what each of these techniques involves.
1. Manual data mapping
Manual data mapping requires professional programmers and data mapping workers – IT will code and map your data sources. While this is a tough job and requires professional help, it gives you complete control and customization of your cards.
2. Semi-automatic data mapping
Semi-automatic data mapping (or schema mapping) requires some programming skills and means your team will switch between manual and automated data mapping processes (hence the name of this technique).
Data mapping software connects the data sources and then an IT professional reviews those connections and makes manual adjustments if necessary.
3. Automated data mapping
Automated data mapping means that one tool takes care of all aspects of the data mapping process for you, making it an ideal option when you have no or no access to a coder. This type of software usually allows drag-and-drop mapping. All you have to do is learn to use (and pay for) the tool.
Speaking of tools that automate the data mapping process for you, next, let’s review some of your options.
Data mapping tools
Data mapping tools and software make the data mapping process easier – including visualizing and interpreting your data. No code is required, they often have a drag-and-drop user interface (UI) and you can implement them on your team regardless of your technical experience. Many data mapping tools can also help you with other data management tasks, such as data migration.
1. Bloomi
Price: Free 30-Day Trial; Contact for a quote.
Bloomi, owned by Dell, is a cloud-native and scalable iPaaS solution that connects both cloud and local data and applications. Design cloud-based integrations the tool calls Atoms. Then you can start transferring data between the cloud and your on-premise apps.
Bloomi’s data mapping function translates electronic data interchange (EDI) for you. The tool has a drag-and-drop user interface that makes data mapping easy, as well as a library of available connectors so you can quickly set up integrations.
2. Tableau
Price: Free 30-Day Trial; $ 12-70 / user / month.
Tableau is a visual analysis and business intelligence platform with data management and data mapping tools. Whether your data is in spreadsheets, Apache Hadoop, databases, the cloud, etc., you can connect to the platform and visualize your data in seconds with no code.
Tableau regularly fills in your latest data (on a schedule that you can customize). The drag-and-drop interface is easy to use and intelligent dashboards enable effective data visualization. Finally, you can easily share your data cards and dashboards with your team on a mobile device for easy alignment and access.
3. Astera
Price: Free 14-Day Trial; Contact for a quote.
Astera is enterprise data management software that uses visual interfaces to convert, map, and validate data structures for you without code.
You can use the tool’s drag-and-drop functionality to create, debug, and manage complex data integration tasks. Astera also natively connects to a wide variety of database providers, including SQL Server, Oracle, and DB2.
To ensure that your data is of the highest quality, there are built-in data cleansing, data profiling, and data quality options – and to improve accuracy, there are built-in transforms that remove duplicate records, complete missing information, and remove redundant data. You will be flagged and emailed if your records do not meet the high data quality standards.
Use the data map for your team
Data mapping can ensure that your marketing team, and your company as a whole, get the most out of your data. It also helps you maintain high quality data and automate the processes of data integration, transfer, migration, and more. Determine what technique you are using and if you need a tool to start mapping data on your team.