Guest post by Kerry Leigh Harrison.
Data mapping—matching fields from one database to another—is the first step in data management tasks, such as data integration and data migration. Before you can analyze data for business insights, you need to homogenize it to make it useful for decision making.
Image credit: Desola Lanre-Ologun on Unsplash
That makes data mapping a critical first step in a number of different analysis processes, which is why software must be chosen with care. Here’s what you need to know about data mapping software, including some of the different solutions on the market today.
What are the benefits of data mapping?
Data mapping is not only vital for keeping your records updated across systems, but it can also help with:
- Spotting emerging trends and taking action faster
- Increasing sales and overall profit by enhancing your customer relations
- Achieving higher efficiency levels in all of your company operations
- Making faster decisions because you have easy access to information
- Getting all of your business information organized
The different types of data mapping
Image credit: Marvin Meyer on Unsplash
There is no single way of going about data mapping; a number of different techniques can be used. Four of the most common techniques are:
- Hand-coded data mapping – This involves data mapping while using procedural code, graphical mapping tools, or creating XSLT transforms.
- Semantic data mapping – Semantic mapping is similar to auto-connect that is regularly used in graphics mapping. The difference is that you cannot use the metadata registry to look up data element synonyms. Semantic is only able to find exact matches between data columns.
- Transformation logic data mapping – This technique is utilized to create applications that are responsible for data mapping.
- Data-driven mapping – This involves assessing data from two different sources simultaneously using statistics and heuristics. The analysis is done to find complex mapping between two sets of data. This is the technique that is most commonly used, as it will find transformations between two data types automatically.
The best data mapping software for visualization and analysis
Here’s a closer look at six popular and capable data mapping solutions.
1. Carto
The first data mapping software application to consider is Carto. It’s known as one of the most powerful yet straightforward data mapping solutions on the market today.
You can connect your spatial data with ease. You can either use remote files or connect to your data warehouse, then add your data and move it using the simple drag-and-drop interface.
Carto enables you to connect your current analytics stack and enrich it with external data from their Data Observatory. You can connect to all of the leading analytics and cloud data platforms, such as Databricks, Amazon Redshift, Snowflake, and Google BigQuery.
Another benefit of going this route is the speed at which you are able to carry out spatial analytics. More than 60 advanced SQL functions are delivered via the Analytical Toolbox, making it quick and easy to carry out location-based analytics using Spatial SQL.
Whether you are looking to detect clusters and outliers, create polygons from points, geocode data, intersect and aggregate, or create travel and distance buffers, you can do so with ease and get powerful insights for your organization to help make better, more informed business decisions.
The Builder also gives you the ability to design maps and reference them in your code using the powerful deck.gl visualization library. Carto will update maps and handle the visualization of large datasets.
2. Altova
A second solution worth evaluating is Altova, which offers a 30-day free trial that so you can get a better feel for whether or not this is right for you.
MapForce is the Altova graphical data mapping tool. It can be used for integrating and mapping any sort of data. Source code or execution file will be generated using this tool for recurring conversions of your data.
You can map, execute, manipulate, and visualize both complex and individual mapping projects.
You can map any sort of data, with common types including Excel, Google Protocol Buffers, XBRL, EDI, SOAP & REST Web services, Database data, Text & flat files, XML, and JSON.
3. Pentaho
This is another reliable, high-quality data mapping tool you may want to consider. Pentaho is a single platform that gives you everything you need to manage your analytical data pipeline.
It is a multi-threaded, scalable data integration engine, which gives you the ability to generate reusable data integration templates.
You can switch with ease between different execution engines, such as Pentaho, Spark, and Apache. It provides robust support for NoSQL, Spark, Hadoop Distributions, and object stores.
The drag-and-drop functionality is a big benefit. It also includes job rollback and restart, as well as performance monitoring.
4. DB Convert
DB Convert is another great software tool for businesses seeking an effective data mapping solution. There are three different license types, depending on your needs and how comprehensive they are. Before committing, you can check out the free trial, which enables you to migrate 50 records for every database table so you can get an idea if this solution is the right option for you.
You can convert and replicate your data between all of the leading databases, such as SQLite, DB2, MS Access, Firebird, PostgreSQL, SQL Server, Oracle, and MySQL. You can also replicate data between numerous Cloud platforms, including Google Cloud SQL, MS Azure SQL, and AWS RDS / Aurora.
Noteworthy features include:
- Scheduling database migration and sync jobs at specific times
- Data filtering
- A graphical interface for mapping data
- Data type changing only for a specified field
- Data types changing for all databases via Global Mapping
5. ZigiOps
A fifth data mapping solution worth looking into is ZigiOps. This is a no-code, highly scalable integration platform, which enables you to smoothly transfer data in real-time. As with some of the platforms above, there’s a free trial, so you can try out the platform before you buy it.
Born from the need to enhance cross-team collaboration and automate processes, ZigiOps runs in the background, transferring data and extracting data between systems in real-time.
Support small businesses. Don’t buy through “review sites” and give your money to Gartner.
The recovery feature protects you from losing valuable data if there is any downtime on your system.
ZigiOps is powerful enough to handle a large number of queries per day. It also offers extensive integration options, as is the case for most of the data mapping solutions mentioned in this post. This means that not only can you capture complex data dependencies, but you can synchronize related entities of any level.
Your team can create integrations without a deep technical background. The template library is very easy to use and easy to access once you are inside the tool.
6. Integrate.io
Integrate.io is a cloud-based ELT, ETL, and data integration platform. It enables you to easily create visualized data pipelines for your data warehouse.
You can integrate data from more than 100 SaaS applications and data stores. Your data can also be integrated with a number of sources like cloud storage services, NoSQL databases, and SQL data stores.
This tool offers connectors for data warehouses, databases, files, and applications. You can also schedule and orchestrate data pipelines with the help of the Integrate.io workflow engine.
Make the most of the best data mapping software to improve visualization and analysis
These six applications are among the best tools available to enhance your data mapping, visualization, and analysis efforts. Each enables you to extract insights to improve your organization’s data-driven decision making.
Kerry Leigh Harrison has over 11+ years of experience as a content writer. She graduated from university with a First Class Hons Degree in Multimedia Journalism. In her spare time, she enjoys attending sports and music events.