Data consolidation: What is it, and why do it?

“Unify” might have become one of the most popular terms in business in recent years (right up there with “data silos”). Yes, they’re buzzwords, and people tend to overuse them. But they are still relevant, mainly because businesses hoard data like a family of ten stockpiling cans of beans ahead of a zombie apocalypse (or just another pandemic).

64% of organizations manage at least one petabyte of data, and 41% surpass that with at least 500 petabytes. It’s challenging to imagine just how much data that is, but to put it into perspective, one petabyte of data is the equivalent of roughly four trillion photos.

The problem isn’t having too much data; it’s not knowing what to do with it. That’s why 68% of business data goes unleveraged. Data consolidation can help: it combines all your scattered information into clear, accessible, usable sources.

What is data consolidation?

Data consolidation is the process of gathering data from multiple scattered sources into a single, central repository. Suppose you run an e-commerce business, for example. Your customer data lives in more places than one. The sales team uses a Customer Relationship Management (CRM) tool to track deals, your operations personnel likely uses an automation tool to handle shipping, and various other platforms for payment processing and customer support. Each system holds different data:

● Your CRM tool might track names, emails, and customer interactions.

● Your payment tool holds credit card details and transaction histories.

● Your e-commerce automation platform manages purchase patterns and preferences.

While some data may overlap (for example, names and email addresses appear in multiple systems), each tool also holds unique information. If your data is everywhere all at once, it’s easy for you to lose track of it, and for it to become outdated, inconsistent, or mismatched. This fragmentation makes it >By consolidating this data into a single repository, you create a “single source of truth” and make information easier to access, manage, and analyze.

The most common data consolidation techniques

1. ETL (Extract, Transform, Load) tools

ETL tools gather data from various sources and adjust it to a consistent format. The process is mostly automated and therefore fast and accurate, so it is ideal for global companies with vast amounts of data to consolidate. Some manual work is involved, particularly in the early stage, as your team would need to manually map the data from different sources and establish rules for handling errors.

2. Customer Data Platforms (CDPs)

CDPs consolidate customer data from multiple systems into unified profiles. They make it easier to personalize marketing, segment audiences, and track real-time engagement. Examples include Segment, Treasure Data, and BlueConic. Because they are more targeted at marketing and sales teams, they may not cover all operational or transactional data outside customer-focused systems.

3. Integration platforms / APIs

Integration platforms and APIs connect different systems so data flows automatically into a central location. They are domain-agnostic and very versatile, so they can connect various data types and use cases.

You may use these to sync customer records from a CRM tool with a marketing platform, or move product and inventory data between e-commerce tools. While they do allow real-time updates and workflow automation, they don’t have the domain-specific intelligence that specialized tools can offer. For instance, you wouldn’t be able to validate data or cross-check it across systems.

4. Data quality, enrichment, and consolidation tools

Even the best data consolidation efforts can fall short if the underlying information is inaccurate or incomplete. Tools in this category cleanse, validate, enrich, and sometimes consolidate data from multiple sources into a reliable single record.

Loqate is a good example: it merges address data from multiple sources into a consistent hierarchy, delivers it via high-performance APIs, and enriches it with metadata like geolocation, timezone, or property type. By combining these tools with CDPs or integration platforms, organizations can build a truly dependable single source of truth.

5. Data virtualization

Typically, data consolidation requires moving information into a central store. But with data virtualization, you get a virtual layer that connects multiple data sources in real time, allowing you to query and analyze them as though they were consolidated in one place (they aren’t).

This method reduces the risk of duplication, cuts storage costs, and provides faster access to up-to-date data without extensive ETL processes. While powerful for flexibility and speed, performance depends on the source systems, and large-scale analytics may still benefit from a data warehouse or lake.

Where to store consolidated data

Now that your data is unified and validated, you have a second problem: where do you keep it? Data warehouses and data lakes are two of the most popular solutions:

1. Data warehouses

Data warehouses are software platforms (either on-premises or cloud) that can store structured, processed data from multiple sources. They are scalable, support complex queries and analytics, and integrate various data streams into a single source of truth. Examples include Snowflake, Amazon Redshift, and Google BigQuery.

2. Data lakes

Data lakes store raw data in its native format, whether structured or unstructured. They can handle massive volumes and diverse types of information, making them ideal for businesses dealing with a mix of data sources. Popular solutions include AWS S3, Azure Data Lake, and Hadoop.

In addition to data warehouses and data lakes, you can store consolidated and validated data directly in operational systems like a CRM tool. This way, your teams can reliably view customer information for day-to-day decision-making and engagement.

Why do you need consolidated data?

You can have all the money in the world, but if you don’t know where it is when you need it, how much value does it bring you? The same principle applies to data. Customer data is clearly valuable for day-to-day operations. For instance, if you run a retail business, your success depends on sending the right parcels to the right customers, and, for that, you need accurate address and contact information. Here are some other key benefits of data consolidation:

1. Improved decision-making

Having an accurate picture of your customers, sales, and operations means you can base your decisions on evidence, not what you think you know. You can make informed strategic decisions about, for example, what products to invest in, how to optimize inventory, and which customer segments to prioritize.

2. More effective marketing

Your marketing will be far more effective if you truly know your customers and their habits and preferences. With a bird's-eye view of this data, you can identify patterns, segment your audience, and personalize your messaging to resonate better while reducing wasted ad spend.

3. Enhanced customer experience

When customer records are consistent across platforms, you can get the basics right: dispatch the right products, get your communications to the intended audience, and avoid wasting time reconciling conflicting information. This efficiency allows your team to respond promptly and deliver a more reliable level of service.

4. Cost reductions

Consolidated data helps cut unnecessary costs across your business. You avoid wasting marketing budget on duplicate or irrelevant campaigns, reduce shipping errors and returns with accurate customer information, and save on operational labour by spending less time reconciling conflicting data.

Why consolidating address data isn’t enough

You likely have so much information about your customers that it could overwhelm you if you looked at it all at once. However, not all data is equally valuable or necessary for your business.

If you operate in sectors like retail, finance, utilities, and gaming (among others), address data is often one of your most critical data points. Accurate, consolidated addresses are more than a back-office nice-to-have: they directly impact operations, customer experience, and business insights.

The consequences of storing wrong or incomplete addresses can escalate quickly. Customers may be frustrated by missing parcels or delayed onboarding, which affects their perception of your brand and damages their trust. Businesses also face additional costs from redirects, refunds, or operational inefficiencies. Depending on the sector, inaccurate customer data could even create compliance gaps.

Plus, unlike names or phone numbers, which are relatively straightforward, addresses contain many components, which increases the likelihood of errors. A single abbreviation, one incorrect digit, or a minor formatting mistake is all it takes for a failed delivery or verification check.

Address cleansing is just one of the many necessary yet complex steps you need to take to ensure addresses are accurate and updated. Each country follows its own rules for address formats, and the more markets you operate in, the more challenging it is to standardize and validate your data.

How Loqate can help you

Loqate’s address verification solution can validate and standardize addresses in real-time, catching errors at the point of entry. That means when you consolidate your data, you already know it’s accurate, avoiding problems before they even start.

If you’re sitting on vast amounts of address data and are unsure how much of it is correct or up-to-date, Loqate can consolidate and cleanse it all at once. Its batch data cleansing service can process up to 100 addresses per second, or 360,000 records per hour, depending on the size and quality of your data.

On top of that, it can also enrich addresses with additional context like geolocation, timezone, and property type, so your data becomes far more useful for analytics, operations, and customer communications.

And if you operate internationally, Loqate’s global coverage across 250+ countries and territories, combined with sub-premise level validation down to apartments, suites, and floor numbers, ensures your addresses are accurate no matter where they come from.

Ready to transform your address data? Request a demo or free trial.