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Technologies that made data mapping no longer a challenge

The best way to determine the most suitable data mapping software for your firm is to do a bit of research.

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Data rules the business world.

Unfortunately, modern organizations have to deal with large data sets from different sources with different formats, languages, and schemas.

To ensure data migrates from its sources to its destinations smoothly, businesses have embraced data mapping.

What Is Data Mapping?

Data mapping is the process of linking and integrating different data sets. This process helps establish relationships between different data models that are from various sources. Data mapping also ensures that the data in the source field matches the one in the destination field.

Data mapping helps homogenize and organize data in a way that decision-makers understand it. The process also allows firms to draw conclusions on the relationships among separate data sets, further helping firms predict actions and results. Data mapping also minimizes errors and redundancies, ensuring more accurate insights and analysis.

In many business environments, the use of manual data mapping is challenging as these organizations have to deal with large data files with many fields that require complex transformations.  Fortunately, with the help of data mapping technologies, mapping such large data sets has become simpler.

But before we look at examples of some of these technologies, let’s review some of the common data mapping techniques.

Data Mapping Techniques

Data mapping techniques are classified into three:

  • Manual data mapping – This is where the firm developers hand-code the data connections from their source to their destination using programming languages. While manual data mapping is flexible as it can be customized to your organization’s needs, it’s also time-consuming, code dependent, and requires lots of resources.
  • Semi-automated or Schema mapping – This mapping technique uses software for data mapping with some human intervention. This method creates a balance of effectiveness and flexibility compared to the manual mapping technique. Unfortunately, it still needs developers to have coding knowledge. It’s also resource-intensive, and developers have to navigate between the automated and manual processes.
  • Automated mapping– Automated data mapping is entirely dependent on automated tools. This method is easy to use as it doesn’t require one to have coding knowledge. It’s also flexible with a low barrier to entry.  The only downside of this mapping technique is that the software may be expensive, and training may be software specific.

Choosing the Right Data Mapping Tool for Your Organization

Automated data mapping software maps data within seconds without the need for human intervention. This saves your organization resources and time.

Data mapping software can be on-premises if the tool is hosted on the firm’s server. It can also be cloud-based if it’s using a cloud-based data integration platform or open-source, often recommended for small businesses with small data volumes.

Here are characteristics to look out for when sourcing for an automated data mapping tool for your firm.

  • Comprehensive systems support where the data mapping software should support more than the basic Excel, XML, JSON file formats.
  • Should have data visualization capabilities that make it easy to interpret data
  • Easy to use code-free automated interface with drag and drop features
  • Ability to automate and schedule data modeling and mapping processes and jobs
  • Customizable software that can adapt to the data mapping needs of a specific organization
  • Ability to generate instant data previews and real-time reports that are also up to date

Technologies That Have Revolutionized the Data Mapping Process

Every organization benefits from reliable data analysis provided by automated data mapping tools. If your firm isn’t already using a data mapping software, it’s time you sourced for one.

Here is a list of some of the best data mapping tools in the market.

1.      Xplenty

This subscription-based data mapping tool offers a 7 days free trial. It’s cloud-based, and it lets you integrate data with different sources such as SQL, NoSQL, and cloud-based storage. You can integrate data from more than 100 sources, and the software can be customized to your organization’s needs.

In addition to data integration, XPlenty also schedules, maintains, monitors, and secures your data.

2.      CData Arc

This cloud-based software can be easily integrated with your firm’s applications and systems. Its user-friendly and intuitive interface offers guidelines on how to use the software.

CData Arc also offers an enterprise-ready architecture with automated connectors for CRM, marketing, data warehouses, and analytics.

3.      Adeptia

Adeptia is a popular data mapping software due to its affordability and flexibility. It has both a web-based and self-service portal enabling it to be used by both partners and customers.

Adeptia also has comprehensive and versatile data mapping capabilities. Its B2B integration platform can integrate customers’ and partners’ data with other applications. It’s also easy to use and set up.

4.      Oracle

Oracle offers cloud-based data integration abilities. It uses API management and machine learning to get value from your data.

This software is particularly suitable for massive data manipulations and integrations. It offers a performance-based design approach, and its data integrator provides uninterrupted access to data from different systems.

5.      Alooma

Alooma offers both cloud-based and SaaS services.

This software has a user-friendly interface, and it supports Snowflake, Amazon Redshift, Periscope, and Google BigQuery data. It also offers real-time insights while also updating the data resources weekly.

6.      Altova

Altova is a graphical data mapping tool that integrates with any data type. It has a vast library of data processing and conversion functions. You can also perform data mapping on this software in a spreadsheet format.

Altova also enables users to import existing data transformation code.

7.    Entity Developer

Entity Developer is a multi-featured ORM designer for Entity Framework, EF Core, NHibernate, and LINQ to SQL, that integrates with Visual Studio seamlessly.

With this tool, users can design and edit entity models from scratch or do reverse engineering from existing databases. A neat GUI allows for working in a visual mode, without manual coding.

In closing, the best way to determine the most suitable data mapping software for your firm is to do a bit of research. Some of the software offer free trials, which can help you test their functionality. You can also read reviews from real customers to determine if the software fits your organization’s mapping needs. 

Have any thoughts on this? Let us know down below in the comments or carry the discussion over to our Twitter or Facebook.

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