Data Mapping Tools
Data Mapping Tools
Keeping track of the data you have in your data warehouse via the use of data mapping tools is essential to any data professional. Check out this great list of tools!
Join the DZone community and get the full member experience.Join For Free
How to Simplify Apache Kafka. Get eBook.
When you're in the process of integrating all your data to be stored in your data warehouse for end-user analysis, it's imperative to map your data. Data mapping translates between one source of information and another, essentially matching data source fields to the target fields in the data warehouse.
The number and complexity of databases, sources, and types of data that have to be consolidated makes data mapping a critical function to extract the most value from your data warehouse, and exact the most accurate insights from your data. Because data mapping plays such an important role in data warehousing, organizations need to decide how data mapping fits into their larger data strategy: to either do the mapping themselves on-premises or use other tools that are available today.
In addition to on-premise tools, there's a bevy of open source and cloud-based data mapping tools available that provide a different level of functionality and support based on your needs.
On-Premise Data Mapping Tools
Large-scale enterprises with major volumes of data can glean some benefit and comfort level from on-premise data mapping tools, especially if there is a concern about security or the need for very fast accessibility. But what you may get in functionality and peace of mind you will also pay for with an exorbitant price tag, additional software to configure alongside existing hardware, and reliance on your IT team to operate.
Here are several on-premise data mapping tools to consider:
- Centerprise Data Integrator
- IBM InfoSphere
- Informatica PowerCenter
- Microsoft SQL
- Talend Data Integration
Open Source Data Mapping Tools
Open source data mapping tools are a typically low-cost way to map your data, ranging from the simplest of interfaces and functionality up to more advanced architecture, and offering online knowledge bases in the way of support. These tools work better for smaller and less complex data sets, as anything larger or more complicated can cause performance slowdowns. Open source tools usually also require some coding skills to get up and running.
Some of the most popular open source data mapping tools include:
Cloud-Based Data Mapping Tools
One benefit of any cloud-based tool is the ability to access information in real-time, and cloud-based data mapping tools are no different. Speed, scalability, and flexibility rule the day in the cloud, allowing you to integrate, map, store, and access all your data from any source and in any format with relative ease, and make decisions and modify schemas based off real-time needs without interrupting data ingestion. Cloud-based tools generally come with expert setup and support to make sure you're getting the most out of the product.
Here are some of the top cloud-based data mapping tools:
- Dell Boomi AtomSphere
- Informatica Cloud Data Integration
- MuleSoft Anypoint Platform
- Oracle Integration Cloud Service
- Talend Cloud Integration
How to Choose the Right Data Mapping Tool
Every organization is different when it comes to existing infrastructure, staff, and goals. To help you choose the right data mapping tool, think about the following factors:
- Data complexity. Cloud-based tools can handle multiple data types and any size data sets, so mapping your data accurately is far less of a concern. Standards and schemas can also be defined and changed along the way without resulting in mismatches or data loss. On-premise tools may be able to handle the heavy lifting of large data volumes but are less flexible in the types of data they can process.
- Cost. After the initial cost to get started, cloud-based tools reap the most benefit over time since they can save on additional equipment and human resources. However, open source tools are a viable option if the resources and budget needed for a commercial option are a concern, or if the data to be mapped is lower in volume and simpler in structure.
- Time and expertise. On-premise tools fall short if you need speed and scalability without human roadblocks. The amount of manpower and expertise needed to manage and optimize data operations is beyond what most IT teams can bear. And while open source tools perform well if set up correctly, they lack in-depth support should you need any coding help. But cloud-based tools offer both speed and scalability in addition to expert setup and support to get your data integration and mapping processes underway quickly.
Published at DZone with permission of Garrett Alley , DZone MVB. See the original article here.
Opinions expressed by DZone contributors are their own.