The benefits of data integration for business owners include:

  • Discovering hidden trends, connections, and insights for smarter data-driven decision-making.

  • Reducing the level of employees’ manual effort, letting them focus on higher-level revenue-generating activities.

  • Improving data quality by removing inaccurate, out-of-date, and duplicate information.

  • Achieving a customer 360 view of the company’s clients and potential clients.

  • Establishing stronger data governance across the organization.

  • Destroying data silos and making information visible to everyone in the business who needs it.

From tiny startups to massive multinationals, nearly every company these days recognizes the power of big data. By efficiently processing and analyzing large amounts of data, organizations can streamline their business processes, gain a competitive advantage over their rivals, optimize the customer experience, and make smarter business decisions.

Although we can all agree on the value of business intelligence and data analytics, far fewer companies have successfully implemented a mature BI and analytics workflow. The first step on the road to BI and analytics is data integration: getting all of your information in a single location for easier analysis and decision-making.

No matter your business size or industry, a well-thought-out data integration strategy can offer a wide range of benefits. Below, we’ll discuss the advantages of data integration for business owners, as well as a number of the real-world use cases of data integration.

Enjoying This Article?

Receive great content weekly with the Integrate.io Newsletter!

Woman Woman

Table of Contents

What is Data Integration?

Data integration is a process that brings together information from different sources in a centralized location, such as a data warehouse or data lake. Once these data sources have been integrated into a single unified view, it’s much easier to run business analytics workloads and get actionable insights to key stakeholders.

These days, the most common workflow for data integration is ETL (extract, transform, load). The ETL data integration process has three steps:

  1. Extracting raw data from disparate sources.

  2. Transforming this information to improve data quality and fit the target schema.

  3. Loading the transformed data into a destination such as a data warehouse or data lake for easier processing and analysis. This target location may be located on-premises or in the cloud.

The types of data included in the data integration process run the gamut from external files and websites to legacy systems and databases. A robust data integration platform must be able to efficiently work with these different systems and data sets and combine them under one roof.

Related Reading: What is Data Integration?

6 Benefits of Data Integration

Of course, data integration isn’t just something that organizations do to pass the time. There is an abundance of benefits of data integration for business owners and companies of all types.

The advantages of data integration for business owners include:

  • Less manual effort: Data integration tools use automation to extract information from different sources and collate them together in a data warehouse. This saves users from having to perform the time-consuming, tedious data integration process themselves manually.

  • Destroying data silos: A “data silo” is an information repository that only one team or department in an organization can access, even if other users would benefit. Data integration platforms can extract information from data silos and make it available to the rest of the business in a centralized location.

  • Better data quality: Data integration is a critical component of data management. For example, you may have the same data record stored in two different places in your IT environment—but one is more up-to-date than the other. By integrating your enterprise data, you’re ensuring that users will always have access to the most high-quality, up-to-date, and accurate data.

  • Customer 360 view: Every business would like to have a customer 360 view of their audience, uniting all of their customer data—from a client’s first visit to your website to their most recent purchase. Data integration brings together information from your CRM (customer relationship management) platform with other data sources, such as ERP (enterprise resource planning) software and customer service tools, to achieve a comprehensive customer 360 view.

  • Stronger data governance: Data governance refers to a framework for establishing a solid data strategy and complying with applicable laws and regulations; it comprises the organization’s people, processes, and technologies and includes everything from data architecture and modeling to data security and privacy. By establishing a defined, automated process for data integration, businesses can help improve their overarching approach to data governance.

  • Greater profitability: In the long run, data integration gives you more visibility into your business operations, helping you make smarter decisions and more accurate forecasts. By integrating your data, you can identify hidden connections, trends, and insights that would have previously gone undiscovered.

Integrate your Data Warehouse today

Turn your data warehouse into a data platform that powers all company decision making and operational systems.

7-day trial • No credit card required

Woman Woman

7 Use Cases of Data Integration for Business Owners

The benefits of data integration for business owners listed above are real, but they may seem abstract for organizations that don’t yet have a full-fledged data integration strategy. In this section, we’ll dive more into the details by discussing some important real-world use cases of data integration.

1. Digitizing the supply chain

According to a study by ToolsGroup, just 7 percent of companies say that they have achieved the digital transformation of their supply chain planning processes, with 58 percent currently exploring the possibility. What’s more, 25 percent of businesses cite data quality as a major barrier to digitizing their supply chain.

Supply chain and logistical issues are crucial yet highly underrated factors in an organization’s bottom line. Delays in delivery, products out of stock, and other problems can all negatively impact the company’s customer experience, support, and profitability.

The good news is that data integration can help digitize and optimize companies’ supply chains. By connecting different applications, refining data quality, and automating the data integration process, businesses can effectively deploy data integration tools to better anticipate and ward off any logistical issues. For example, Ecommerce websites can integrate their product databases with their ERP software to ensure that new items are reordered when stock levels run low.

2. Improving marketing efforts

These days, marketing teams need to excel across a wide range of domains. In addition to digital channels such as social media, SEO (search engine optimization), and email marketing, there are also more traditional methods such as direct selling and print and TV advertising.

With so many activities on their plate, marketing teams understandably have a great deal of data to collect and mine for actionable insights. Without a data integration strategy, your marketing efforts will miss promising development opportunities and hidden trends that could help you stay ahead of the pack.

An end-to-end data integration platform can help unite all of the information your marketing team members need to do their jobs. The marketing tools that may be part of your data integration pipeline include CRM software (such as Salesforce, HubSpot, and Zoho), as well as tools for lead generation, website analytics, social media, content marketing, and more.

3. Machine learning and artificial intelligence

Data science, machine learning, and AI have revolutionized the way that companies handle and analyze their enterprise data. These techniques use vast quantities of information (known as “big data”) to learn from their mistakes and develop models that can most accurately predict the world around them.

Of course, for the best results, machine learning and AI models usually need access to as much data as possible. The problem is that these training data sets may be located in many different places and take many different forms.

Unstructured data, for example, consists of files such as text, images, and videos that can’t fit neatly inside a traditional relational database. Streaming real-time data, meanwhile, arrives so quickly that it needs to be handled and analyzed almost as soon as it arrives. To be used in machine learning and AI workflows, all this enterprise data needs to be processed, cleaned up, and integrated in a single location—and that’s exactly where data integration tools come in.

4. Building cross-functional teams

As discussed above, data silos are one harmful consequence when different teams and departments keep information to themselves. Yet the consequences of not sharing data can be damaging even without intentionally meaning to do so.

For example, there should naturally be a great deal of alignment between your sales and marketing teams. However, if these two departments don’t coordinate and exchange information, it’s easy for wires to get crossed. For example, your sales team might approach the term “new customer” in one way, while your marketing team could have a completely different definition (e.g., the length of time since the user’s first purchase).

Data integration helps get everyone in your organization on the same page by collecting information from across the enterprise. This helps reduce duplicate data sets, refresh out-of-date information, and establish a single source of truth that all employees can work from. In turn, this makes it much easier to build cross-functional teams with members from different departments, each with their own data repositories.

5. Real-time predictions and anomaly detection

ETL and data integration workloads to a data warehouse usually occur at regular intervals—for example, overnight, so that key decision-makers can have a report on their desk the next morning.. However, many organizations need to operate in a faster time frame.

For example, credit card companies need to analyze massive quantities of data in near real-time to identify suspicious activity, which could be a fraudulent user. Another example of the need for real-time data integration is in manufacturing, where anomalous sensor data could indicate that a component is broken or overheating. Real-time data integration helps companies make accurate, timely decisions for a wide variety of use cases.

6. Avoiding cloud vendor lock-in

For businesses that want to use cloud computing, the good news is that there’s no shortage of public cloud providers on the market—from Amazon Web Services and Microsoft Azure to Oracle and Google Cloud Platform. Each one of these cloud vendors offers a wide range of services to suit the needs of organizations large and small, from data storage to business intelligence and analytics.

If you’re not careful, however, it’s easy to suffer from the issue of cloud vendor lock-in, in which providers make it much simpler to start using their services than they do to terminate the contract. For example, many public cloud providers charge a higher fee for migrating data out of their data warehouse than they do to ingest it in the first place.

Clever use of data integration can help you avoid many of the problems with vendor lock-in. For example, you can maintain the same data in storage in two different cloud environments or data warehouses, such as Amazon Redshift and Google BigQuery, and use them for different BI and analytics workloads. If you later want to scale your usage of either provider up or down, you can easily do so without the stress of complicated data migration.

7. Data replication and backups

The term “data integration” is used for any process that ingests files and moves them to a centralized location. While a specialized business intelligence repository such as a data warehouse is the most common destination, it doesn’t necessarily have to be the only one.

Indeed, data integration tools can also be used to perform data replication: duplicating files and data in one location and moving them unaltered to another. In essence, this can be viewed as a truncated version of the ETL pipeline in which most of the work is during the extraction and loading phases, with little to no transformation performed.

Performing data replication at regular intervals can ensure that your organization maintains backups of the most mission-critical information. Data replication is also performed to verify that files in different locations (e.g., on different computers or servers) are consistent or identical across the IT environment.

Enjoying This Article?

Receive great content weekly with the Integrate.io Newsletter!

Woman Woman

How Integrate.io Can Help with Data Integration for Business Owners

We’ve discussed the many benefits and use cases of data integration for business owners. There’s just one question left to answer: what’s the right data integration tool for the job?

If you’re looking for an enterprise-grade yet user-friendly ETL and data integration platform, Integrate.io can help. Integrate.io makes it easy for any business owner to leverage the power of data integration.

The Integrate.io platform offers a simple, no-code, visual drag-and-drop interface so that even non-technical business users can get started building and deploying their own data pipelines. What’s more, Integrate.io comes packed with more than 140 pre-built connectors for the most popular third-party software and tools—from Salesforce and Google Analytics to a standard REST API.

It’s never been simpler for business owners to make better-informed decisions with Integrate.io’s data integration software. The Integrate.io data integration solution includes many useful features to make your ETL workflow as fast and efficient as possible.

For example, Integrate.io’s FlyData CDC (change data capture) functionality ensures that the next data integration job you run will only capture changed or new data and not the entire database. Integrate.io also supports reverse ETL, i.e., moving data out of a centralized location to third-party systems for easier access and analysis.

Ready to learn how the Integrate.io data integration platform can benefit your organization? Get in touch with our team of data integration experts today for a chat about your business needs and objectives or to start your intro call to the Integrate.io platform.