Chances are, your business collects more data than it knows what to do with. With a large variety of data sources, all amassing enormous amounts of data, but without anywhere to put it, you’re likely missing information critical to the success of your business. 

Implementing a data consolidation strategy can help you make the most of your data. This article will explore data consolidation, why it’s critical to your business, various data consolidation techniques and how to get started. 

What is data consolidation?

Data consolidation is the process of consolidating data from multiple sources into a single destination. During the consolidation of data process, different data sources are put together into a single data store. This process is sometimes also referred to as data integration.

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Data consolidation is primarily used by businesses that have significant amounts of data that are stored in different and often disparate sources. These businesses want to be able to understand, analyze and use their data to inform critical decisions. For this purpose, their data must first be consolidated into a single, readable and actionable data store.

Why is data consolidation important?

There are a few key reasons why businesses with growing amounts of data choose to consolidate their data. Let’s take a closer look.

Reduces costs

By consolidating all of your data from disparate sources into a single location, you can eliminate redundancy in your data reporting and reduce inaccuracies within that data. 

Having consolidated data also means you can better operationalize that data. Creating a single source of truth for all of the data you collect offers vast benefits to reducing your operational costs. 

With consolidated data centrally located and accessible with business analytics tools, you can uncover where your company is misspending or overspending money. Insights like these can have a big impact on your bottom line. 

Utilizing accurate, comprehensive and easily accessible data means that you can better analyze past revenues and predict future growth or contractions in certain business segments. In short, more reliable data means more reliable revenue for your company.

Saves time

By having all of your critical data at your fingertips, you don’t have to manually search through a range of sources to find the information you need. Consolidated data that is made readily available in a single location store like a data warehouse can be queried and retrieved easily by operations personnel and shared across your company to all departments who need it. 

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Having a 360-degree view of your data outputs can give you improved business intelligence about your day-to-day operations, management processes and operational insights.

Enhances decision-making

Data consolidation can also improve decision-making processes across your business. The more accurate your data is, the more confident your decision-making will be. Implementing data sharing alongside data consolidation means that personnel in departments across your organization can benefit from having access to accurate and relevant data. Those benefits can also be offloaded onto front-facing customer interactions as well. Understanding your customers better with accurate and easily on-hand data means that you can provide them with better and more timely customer experiences. 

These are just a few of the reasons why it's important to consolidate data. Still, each business is unique, and data operations leaders at your organization may have their own reasons for wanting better data consolidation practices. 

Data consolidation techniques

Depending on how much data you regularly collect and store and what you want to do with your data once it’s consolidated, there are a few different data consolidation techniques to consider when rolling out your new processes.

Extract, Transform, Load (ETL)

The first data consolidation process is what’s known as an Extract, Transform, Load (ETL) process. In short, an ETL process involves extracting data from various sources, transforming it into a standardized format and loading it into a destination. 

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There are two different ways of deploying an ETL process for data consolidation, as well as an innovative variation on traditional ETL architecture known as Extract, Load, Transform (ELT). 

Hand-coding

For small, uncomplicated data consolidation tasks, you can use a hand-coding consolidation technique. This is done by a data engineer, who scripts a code that will send your data from disparate sources into one central location.

ETL tooling

The most common way that data is consolidated is through a process called ETL. For more complex jobs, it’s more cost-effective to use an ETL tool than to hand-code a solution to consolidate your data. These tools retrieve your data from different sources, transform into a unified format and load into a destination such as a data warehouse or a data lake.

A new process: ELT

Fivetran has developed a process of data consolidation that is more flexible than traditional models of ETL, which is Extract, Load, Transform (ELT). With ELT, data is extracted and then loaded into a centralized staging area. Only then is it transformed using schema. Since the data has been pre-loaded already, it can be transformed into different formats that analysts can use to inform business decisions. ELT is data consolidation for the agile, modern age. 

With Fivetran, you can utilize expertly designed APIs, pre-built transformations and data pipelines to build your consolidation process. ELT at Fivetran is also reliable, scalable and robust compared to the older models of ETL processing which are fragile and inflexible.  

Data virtualization

Another possible method of consolidating your data is using data virtualization. With this process, data remains siloed in its original sources and a virtualization layer is applied across each data source to bring together that information. 

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Unlike ETL or ELT, the data remains unchanged and is simply viewed through a central lens. But the problem with data virtualization is its limited scalability and inability to consolidate large amounts of data. There is also a limited capability of data virtualization tools to produce comprehensive reporting and analysis. 

Data warehousing

A data warehouse is a central repository that contains all of your collected data from all of your data sources. 

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There are three main components to a data warehouse:

• The bottom tier, which is where the data is held
• The middle tier, which holds the analytics engine
• The top tier, which is where your data is viewed, analyzed and reported on

Data warehouses provide a broad view of company data that can be accessed holistically and uniformly represent your relevant data. Ultimately, the best way to consolidate your data into a data warehouse is through automated ETL tools like Fivetran.

How to get started with data consolidation

Follow these steps to get started with your new data consolidation process.

1. Identify possible challenges and resources

The first thing to consider is what possible challenges you may run into as you deploy a data consolidation process. Taking stock of what data sources you want to pull information from is a good first step. Knowing how that data is currently stored can help you head off any challenges that might arise when you start to transform and consolidate that data. 

Taking a full inventory of your data assets can also help you understand if you have any legacy infrastructure that will have difficulties connecting to a modern data pipeline or data stored in ways that can’t easily be extracted. This will help you determine if you need professional assistance consolidating your data. 

2. Consider professional services for data consolidation

It may be necessary to consult a data professional for more complicated configurations or data requirements. You could hire a dedicated data engineer to build a data consolidation process from scratch. 

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Alternatively, you could engage with a team of data professionals and take advantage of robust, pre-built solutions that are flexible and scalable enough to work with your unique requirements. 

Ensure your data team considers all aspects of your data consolidation requirements. That includes any data compliance needs you must meet, as well as data replication and backups to ensure no accidental data loss occurs. 

3. Use an ELT tool

If you have more than a small amount of data or are planning on collecting more data, you should automate your data consolidation practice with an ELT tool. Using an ELT tool streamlines the process of data consolidation. Once fully configured, your ELT processes work quietly and consistently in the background, bringing data in from disparate sources, transforming it using pre-set rules and loading it seamlessly into your destination of choice. If you’re unsure where to start, Fivetran can help you get on the road to better data consolidation with ELT.

4. Make a data consolidation plan

It’s now time to make a data consolidation plan. Bring together all the information you have about your data sources and identify any potential challenges you may run into. Then determine whether you’ll use an automated tool to build your data pipeline.

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Define your project timelines and leverage your resources to build your data consolidation architecture. Test, test and test again until you’re ready to deploy your new data consolidation process. Finally, launch your new data consolidation process and take advantage of the enhanced analytics and reporting benefits. 

Conclusion

As data proves to be a critical asset for all modern businesses that want to grow and succeed, ensuring that you make the most of your data collection with a streamlined data consolidation process is crucial.

While there are many techniques and elements for data consolidation, using an ELT process is the best way to get the most out of your data and improve your business processes, outlook and strategy. Tools that help you process and understand your data faster are here to help.

Understanding data consolidation and its importance to your business is the first step to making data the cornerstone of your business’ success. Ready to get started? Start a free 14-day trial today to learn how Fivetran can help you consolidate your data with fully managed and automated data pipelines.

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