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Everything to Know About Data Consolidation

  • Written By: Cheyenne Kolosky
Data Consolidation

In this data-driven age we live in, being able to bring together information from all the various sources it lives has become an absolute must for businesses wanting to understand what’s going on – with their operations, their customers, their industry, and their business performance overall.

Data consolidation is one of those major pain points when it comes to streamlining business processes, having a solid data backup plan, and leveling up the entire enterprise data management practice.

Key Takeaways

  • Data consolidation means combining data from multiple sources into one unified, consistent format for analyzing and making decisions.
  • Nailing an effective data consolidation strategy leads to more efficient operations, smarter business intelligence, and better decision-making.
  • Methodologies like ETL and ELT are hugely important for data consolidation, each with its strengths and situations for which it works best.

What is Data Consolidation?

Data consolidation is the process of taking data from all the different places it lives – various systems, applications, third-party sources, etc. – and combining it into one standardized, unified format to analyze and make decisions from.

Data consolidation allows you to compare and analyze your performance across multiple aspects of your business simultaneously, offering actionable insights and a potential competitive advantage over your competitors. 

In today’s world, where data is essentially the new oil, consolidating all that raw information is critical for businesses to get a complete picture of how things are running, who their customers are, and what’s happening in their market.

Data Consolidation vs Data Integration

Though these two terms are often used interchangeably, they’re different things. Data integration is the big-picture process of combining data from different sources. Data consolidation is a specific part focused on merging and standardizing data into one unified analysis and reporting format.

Data Consolidation Techniques

There are two primary methods for data consolidation which are ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform).

  • With ETL, you extract data from the sources, transform it into a consistent format, and then load it into the target system, such as a data warehouse.
  • ELT flips that a bit—you extract and load the raw data first, then transform it as needed once it’s in the target. Which one is better depends on data volume, complexity, and performance needs.

Setting Up an ETL Pipeline

To start an ETL pipeline, you’ll need an ETL tool. First, identify your data sources and the target system (data warehouse, data lake, etc.). Define what transformations must happen—cleaning, deduping, standardizing formats, etc. Then, schedule the ETL process to run regularly or in real-time, depending on your needs.

ETL Processing Methods

There are two ways to process with ETL: batch and real-time. Batch is extracting, transforming, and loading the data in set batches, like daily or weekly. Real-time uses Change Data Capture to identify and propagate data changes immediately, so the target is always up-to-date with the latest source data.

Examples of ETL in Action

Here are a few typical examples of companies utilizing ETL:

ETL for Data Warehousing

  • ETL is super common for pulling both historical data and current data into data warehouses
  • Data warehouses combine historical and transactional data from all over an organization
  • ETL makes sure that data gets extracted, transformed to a consistent format, and loaded into the warehouse properly for analysis

Data Migrations

  • ETL tools can facilitate data migrations from one platform to another, giving you more insights.  
  • Using ETL makes migrating data way quicker and easier than trying to do it manually

Data Integration

  • ETL is critical for integrating data between organizations using different data sources and formats
  • It standardizes everything into one common format to load into a shared repository for product managers and other appropriate team members.
  • Enables much smoother data management and decision-making

Third-Party Data

  • Large operations utilize different software vendors for different purposes, such as billings, CRM, and more. 
  • ETL can incorporate data from one dataset to another, allowing you to gain actionable insights into your operations and seamlessly allowing different systems to integrate.  
  • With ETL, you can integrate various third-party sources of data seamlessly into one place. 

Data Consolidation Best Practices

To maximize your ROI on data consolidation, it’s worthwhile to implement certain practices to give you maximum oversight and clarity.

Here are some important best practices you should note: 

  • Transformation: Make sure data types are compatible with the consolidation target system and transform any differences in format, units, etc.
  • Data Copies & Lineage: Keep copies and track where data came from and what it went through to aid compliance, auditing, and confident decision-making.
  • Character Set Conversions: Standardize those conversions so single-byte characters are consistent to avoid errors when consolidating.

Data Consolidation Benefits for Businesses

Incorporating data consolidation into your business has numerous advantages.

Here are a few of the top benefits: 

Operational Efficiency

With consolidated data from all sources, businesses can streamline and cut redundancies for leaner operations. A complete view of operations and performance metrics enables smarter decisions and better resource allocation.

With effective data consolidation, you can have more clarity into where the best place to invest funds is for the coming years. You can identify where you are getting the best ROI and make strategic plans on how to best take advantage of this information.

Boost to Productivity

When you have clear data consolidation, you can monitor employee performance across all departments of your organization. As such, you can identify when employees’ performance drops, allowing you to quickly take action to boost morale or reallocate some tasks to boost employee output. This real-time insight allows you to maximize productivity in your operations. 

Planning & Strategy

Having that unified dataset is a total game-changer for planning and executing strategies effectively. Identify trends, customer needs, and bottlenecks to drive the business forward with pinpoint, accurate intel. 

Reliable information is essential for strategic planning. Without accurate consolidated data, strategic planning is unlikely to be effective, as data is required to make realistic predictions of market trends, dips in production, etc. 

Data Consolidation Challenges 

Data consolidation being incorporated into your operations can also pose a number of challenges for your organization. Here are some issues businesses can face when consolidating data:

Resource Constraints 

Data engineers and analysts have limited resources, as manually coded consolidation techniques are time and labor-intensive. Your data engineers need resources to install and maintain the system, and the cost of their labor only increases as you add more sources of data. 

More Than One Location

Storing data can pose a challenge to businesses, especially given the fact most businesses store data in more than one location. As a result, there can be lags and inefficiencies when different locations communicate with each other due to bandwidth and time constraints. 


Another major concern when using data is security. The best practice is to secure your data in a secure location, but this is expensive. Storing your data off-site can be more affordable, but it is not without additional risks of data breaches. 

Data Consolidation Use Cases

Data consolidation is leveraged across various industries by companies, small to large, to gain a competitive advantage over the competition. Below are some common use cases for data consolidation software, with template apps included to make implementing data consolidation more straightforward: 

  1. Inventory Management: Inventory management data consolidation allows e-stores, as well as brick-and-mortar stores, to keep track of what they have. This ensures store owners know how much stock they have and what they may need at any given moment; optimizing the inventory management process.
  2. Customer Portal: Customer portal data consolation allows you to facilitate self-service processes for your customers. Customer portals can be used to keep your customers informed with key data while allowing them to upload their own information. This improves your communication and establishes trust among your customer base. 
  3. Construction Management: Construction projects are complex and require constant streams of data to keep everything on track and running on time. You can leverage data consolidation to track everything in a construction project, from managing team members, tracking inventory of building materials, updating suppliers on needs, informing stakeholders on building progress, and more. Bring together all project data from teams, suppliers, contractors, etc.
  4. Government Procurement: Government procurement involves the acquisition of goods and services by public sector organizations to carry out operations. This often involves dealing with large volumes of data from different departments, vendors, projects, and budget allocations. Data consolidation can significantly help streamline procurement processes for government agencies. It allows them to maintain a centralized repository of all procurement-related data, including vendor master records, contracts, purchase orders, invoices, item catalogs, and prices. 
  5. Document Management: Managing documents is another useful application of data consolidation that streamlines the organization, storage, and retrieval of important documents. This facilitates easy searching for information, as well as seamlessly allowing your team to create and manage documents, improving operational efficiency across your organizations. 

Knack’s No-Code Data Consolidation Solutions

Knack is a powerful no-code solution for teams of all sizes. With native integrations and user-friendly data transformation capabilities, you’ll be able to build custom software solutions for your business for a fraction of the cost. Whether you’re consolidating spreadsheets, databases, apps, or anything else, we’re the tools to make it happen seamlessly for your specific needs.

Start building for free with Knack today!

Data Consolidation FAQs 

  1. How do you consolidate data?

Data consolidation is the practice of combining information from multiple sources into a single dataset. Data consolidation can be done manually, or it can be done using software programs and ETL tools.

  1. What are some common data consolidation techniques?

Common techniques for data consolidation include migration, integration, visualization, and management. Each involves extracting data from multiple sources before transforming it into a consistent format and loading it into a centralized dataset. 

  1. What is an example of data consolidation? 

An example of data consolidation is a retail company with a few store locations consolidating data from each store’s marketing efforts, sales, point-of-sale systems, and more to gain actionable insights. This allows them to view and analyze sales data across all locations in a unified manner, facilitating better decision-making. 

  1. What are the advantages of data consolidation?

Data consolidation offers numerous advantages to organizations including improved insight into operations, better data accessibility and visibility, more accurate analytics and reduced bottlenecks in your operations. It also facilitates better decision making through data-driven conclusions.