What is Data Management? Services, Solutions, & Software

June 26, 2024  

A solid data management strategy is the foundation for everything in data analytics. Without good data management solutions in place, any effort to make your data useful and valuable will be ad hoc and limited in effectiveness. 

Data management includes data centralization, data consolidation, and combining data from all your operational systems and databases. By bringing all your data together it gives you a single, unified, comprehensive picture of your customers and operations. With that unified view, you can make decisions and deliver reports, dashboards, and insights to your customers and internal audiences.

First, let’s discuss the foundational principles behind data management.

Overview of data management

What is data management?

Data management is the formalized practice of treating data as an asset and managing it with the same rigor used for managing other financial assets.

Formal does not necessarily mean complicated or heavy-handed. Making formal decisions such as how to organize data sets and who can access them are both actions that fall under data management.

What is data consolidation?

Data consolidation means bringing all data together in a way that it can be analyzed as a single, larger data set. This is especially valuable in modern businesses because they operate across many different products and tools. This reality results in many data silos.

With data living in many different places, it is impossible to get answers to comprehensive questions about your business or customers. 

Data consolidation involves:

  1. Getting data out of its many siloes

  2. Centralizing it into a single database, warehouse, or lake

  3. Combining data into a single, unified model

What is data centralization?

Data centralization is bringing data from multiple silos into a single, central location. Data centralization is part of data consolidation and is an important step to unlock enterprise reporting and analytics.

Data management tools are built around the process of data centralization, as this is a key step in being able to report on consolidated data.

What is a data lake?

A data lake is a strategy for data centralization. It is a central location to store data that originated from various operational systems, databases, or other data silos.

Typically, data lakes are a place to upload files in a semi-organized way. Also typical is some process downstream of the data lake to actually make sense of and combine these data files.

Compared to a data warehouse, a data lake is not as structured. Data lake solutions are more of a “landing zone” or “dumping ground.” than a full solution to analyze centralized data.

What is data lake vs data warehouse?

Both are strategies to centralize and consolidate data for reporting and analytics. A data lake is designed to be an easy way to get data from operational systems and other data silos into a central location.

In contrast, data warehouse solutions are designed to query and report on consolidated data.

Muddying the waters here is that often a data lake will provide some querying capabilities. And some data warehouses are easier than others to load data into. That means there is some overlap in their capabilities.

Nor are these two strategies mutually exclusive. If you have to decide between the two, a warehouse is a more foundational technology, while a data lake is more specialized.

At Datateer, we use both! The data lake makes it easy to get data into a central place. Our data lake is integrated into the warehouse, so we get the best of both approaches.

Learn more about it in our Data Lake vs Data Warehouse vs Data Mart article.

Data management services

Common Data Management Services

Data Consolidation

Whether you need to consolidate and combine data from multiple sources, organize data in a structured manner, or ensure its accuracy, using a data consolidation platform provides the tools and expertise to streamline the process.

Many service providers leverage a combination of cutting-edge commercial and trusted open-source tools for centralizing data, including data warehouse software, to efficiently extract data from diverse sources such as SaaS applications, APIs, and databases. You should look for a data management solution that’s centered around an approach of incremental data extraction, which not only reduces costs but also significantly boosts performance by focusing solely on new and updated data.

CTA: Contact Us about Data Management, Consolidation, & Centralization

Data Centralization

Data management solutions generally include combining data from various sources, centralizing it into a unified view of your business operations and customers. If built on leading data warehouse software, you will have real-time access when you need it.

By centralizing and consolidating data, it will give you a comprehensive view of your customers and operations.

Most data centralization happens in a data warehouse. A data warehouse is just a database. It can be queried like any other database. The difference is it is designed to handle large analytical queries. Cloud technology enables better scalability, so most modern data warehouses are “cloud native” or built around cloud technologies.

With all your data stored in a data warehouse, it can be easily queried using standard SQL. This means it's compatible with most BI tools, data management software, visualization platforms, and data query products. 

Custom Data Management Solutions

Data management solutions should be meticulously designed to cater to the distinctive requirements of your specific business needs. A unique blend of advanced automated systems complemented by expert consulting and services is what makes great managed analytics services

At the heart of a good data management platform are industry-leading commercial tools, which include cutting-edge data warehouse software, ensuring that most integrations work seamlessly 'out of the box'. 

We recommend looking for a service provider with pricing that is transparent and scales with your needs. Here at Datateer costs are determined by the number of Data Assets under Management, granting you the flexibility to adjust the scope of what we manage based on your evolving requirements.

Data Management As A Service (DMaaS)

Otherwise called “Managed Analytics,” DMaaS has you signing up with a partner/vendor who will perform all the data engineering tasks above and let you pay a reliable, consistent, monthly or annual fee. 

Managed Analytics/DMaaS may encompass your entire data stack or just one or two areas. For example, you may have an in-house BI tool for reporting, but you could look to a managed analytics company to build, maintain, and monitor your data pipelines and data warehouses. 

What to look for in your data management solution

Qualities You Should Look For In Your Data Management Solution

Scalability 

As your business grows, so does the complexity and volume of your data. Any software, tool, or solution you select should have a platform that can handle the challenges of scale. Large businesses are managing hundreds of billions of records spanning multiple terabytes, and while most aren't operating at that magnitude, your data management platform should be ready for those who are. To ensure swift performance, focus on extracting only new and updated data. 

Integration

Integration is key in today's diverse tech landscape. The data management platform you select should be fully compatible with a broad spectrum of analytics tools, visualization products, and data management products. 

Can Handle High Demand

In terms of handling demand, we recommend looking for a solution that is backed by the robust infrastructure of Google Cloud Platform and Amazon Web Services. This should allow you to scale to hundreds of parallel nodes for particularly expansive data sources, ensuring that peak loads and high-query demands are met with consistent performance.

In Summary

Effective data management is crucial for leveraging data as a valuable asset, involving processes like data centralization, consolidation, and the use of advanced tools to provide a unified view of operations and customer interactions. 

It's essential to select data management solutions that offer scalability, integration capabilities, and have the ability to handle high demand. 

Finally, as businesses grow, the complexity and volume of data increase, so seeking a managed analytics provider by paying them monthly or annually for Data Management as a Service (DMass) might be a better option than continually trying to manage all of these systems on your own. Datateer is here for all of your data management needs, contact us now by filling out the form below.

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Adam Roderick

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About the Author

Adam's tech career spans startups to global firms, touching finance, tourism, e-commerce, and consulting. Spotting a way to give small- and medium-sized companies an advantage with data, he founded Datateer to democratize analytics. He values relentless progress, simplifying complexity, and putting people first.

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