We live in a time in which information is the core element of business success for companies in almost any industry. Data is the key to making proper and timely decisions, building winning strategies, data can impact everything from revenue growth to customer satisfaction.

According to McKinsey, companies that heavily rely on data and make informed decisions are:

• increasing profits by 93%;
• boosting sales by 82%; and
• improving the speed of sales growth by 112%.

To obtain the necessary information, there are two primary challenges that need to be solved. First is the pace – the information must be provided as soon as possible, preferably in real-time. The second is trustable information you can take action on without questioning it. That’s a big problem, because almost half of data records contain errors that could mess up processes.

So, there is a lot of hype around technologies like Artificial Intelligence, Machine Learning, Cloud Computing, and the Internet of Things — but to benefit from them, companies should embrace digital transformation to its fullest. Right now, nearly 60% of data in companies is inaccessible for decision-making; analysts spend most of their time extracting and processing data. The real cost of poor data quality for businesses is $15 million a year on average.

The solution to all of those problems and challenges, as well as the key to unlocking the value of innovations in technology, is a data integration strategy. It is the only way for businesses to obtain accurate and detailed information that leaders will be able to take action upon.

Data integration is not just a list of technical processes, but rather a whole strategy that will make the necessary information accessible and understandable to anyone in every branch of a business. In this article, we will discuss what data integration is, how to achieve it, what tools we can use, and how to get the most out of your time and budget investments.

“The goal is to turn data into information, and information into insight.” – Carly Fiorina, former executive, president, and chair of HP.

What is Data Integration?

The definition of data integration is pretty simple – it is a process that aims to combine data from multiple sources into a unified view, making it accessible and actionable. You can measure the positive result of this process by getting information fast, accurate, and at scale, which will help you achieve your business goals and maximize your ability to use the latest technologies in your organization.

There is no unified approach or method to data integration, but all solutions have certain parts in common — such as a network of data sources, a master server, and users who need to access data from this server.

To give you an example, typically:

• a user sends a data request to the master server;
• the server collects the required data from both internal and external sources; and
• after extraction, data is unified in a cohesive form and presented to the user.

In most cases, information needs to be unified from a variety of sources before it can actually be used for any kind of analysis. Without data unification, creating a report could involve using information from different accounts on multiple websites, extracting data from apps, copying, reformatting, sorting, cleaning, and processing. After all of those moves, then the analysis could start. That’s where data integration comes into play.

Why is Data Integration So Important?

First and foremost, it saves time on analyzing data and extracting value from it. Your employees will have access to the whole system without a time-consuming necessity to build connections between different subsystems. If you add automated tools for integration instead of manual coding, you can double the productivity of the organization — as 86% of the companies that used these tools did.

Collaboration and data sharing between different departments will instantly improve, despite their location or a project they are working on. Additionally, data integration will reduce the number of errors that could occur — automated solutions that regularly synchronize for updates prevent a lot of possible errors, boosting overall productivity as a result. But there are definitely even more benefits for businesses. Let’s look at them closely.

Top Reasons to Have a Data Integration Strategy

Your information has the power to boost business efficiency to the max, and make all departments work as the one unit. To achieve this, you need to connect all the dots in your plan. Precise planning and excellent execution will take time, but it is worth it. Here’s why:

Keeping up with the data revolution

Without a shadow of a doubt, your leading competitors on the market are most likely data-driven and looking forward to introducing innovation in their organizations. Industries like Finance, Retail, Manufacturing, Healthcare, or Food and Beverage could all be transformed and improved upon based on solutions that involve processing information. Winners do all they can to extract valuable and actionable insights that add to production, logistics, customer experience, brand image, marketing, and the future of the company. Sensors, networking, and cloud storage are cheaper than ever, resulting in an enormous amount of available information. Artificial Intelligence and Machine Learning technologies can make sense of all of that, with capacities far beyond human capabilities. All that needs to be done is unify data from all sources, and the algorithms will work their magic!

Making data accessible

Available data is an advantage for your business; it’s as simple as that! Imagine that anyone in your company, or even your business partners, could have access to centralized information. It will be much easier and encouraging for your personnel to make reports and keep all processes up to date. Alpine Shire Council made a solution in which a wide range of complex information in multiple formats and even digital elevation models are unified. Integrated information is calculated to yield spatial and non-spatial results, and you can access it without delays using an iPad app.

Eliminating security issues

Having access to all possible types of information that is regularly updated and synchronized makes it much easier to provide a higher level of security and prevent fraud. You can implement Artificial Intelligence and Machine Learning solutions to analyze any suspicious activity and have the opportunity to deal with it or you can even set automated algorithms to do it for you.

Improving data clarity

Browsing thousands of interfaces from different types of software is not easy or effective for any enterprise. With a data integration plan, you can optimize all of this and handle complexity while achieving maximum results and the best information delivery. The solution may require an accessible data hub that is easy to connect with. Going back to graphics, Shell Canada is making a 3D PDF dataset out of 2D, 3D, vector, and raster information easily accessible.

Making data more valuable

Data integration adds value to the data; that’s one of the main reasons to have a data integration strategy in the first place. Data quality techniques are becoming more common in DI solutions; these techniques detect the problems that need fixing and improve data characteristics to make data cleaner, more consistent, and more complete. The resulting datasets become much more valuable than raw data, because they are aggregated and calculated. Much like in manufacturing, data integration turns raw material (data) into an actual product (new datasets).

Simplifying data collaboration

Integrated and accessible information opens up an entirely new world of possibilities for collaboration in and out of the company. Basically, anyone who is relying on your information will have a much more effective impact on the processes with the available data in the right format. People with whom you share this data can include internal teams, the whole company, and even your partners — with quick access to information from different sources, your organization will get a precise understanding of the current situation. In the United States of America, the State of Indiana was unifying the information of almost a hundred counties; the parameters included boundaries, parcels, points, streets, and addresses. As a result, all those data points were combined in an online GIS portal, making it convenient for each county as well as centralized and effective for the state government.

Keeping data up to date

An integrated data strategy makes it possible to have information updates as soon as possible. If you include in your strategy cloud technologies, which we will talk about later, it could even be updated in real-time. There is a term “data silo,” which means a steady and isolated repository of information. Because of this isolation, the information is at risk of becoming outdated and inaccessible for collaboration. Data integration techniques will connect those silos in various areas of your business and offer you the maximum potential value out of it.

Fueling smarter business decisions

Organized repositories with a variety of integrated datasets will enable you and your peers to obtain an impressive level of transparency and understanding across the entire organization. Never before accessible nuances and facts about data will now be in your hands, helping you make the right moves just in time.

Business Initiatives that Could Use Data Integration

After our discussion of the reasons to obtain integrated data systems, let’s discuss how you can use it in particular cases.

ETL and ELT Management

ETL stands for “extract, transform, and load” — this is one of the key processes in any data integration strategy. It means extracting data from particular sources, transforming information to some unified format that is required for a certain business goal, and loading data in a new format to the data warehouse. This traditional way to do this is changing, as the Extract, Load and Transform (ELT) approach is gaining more popularity.

Summary

Why is data integration important?

You will get a complete understanding of the information you have in your company and will have tools to drive insights out of it.

How could it help the businesses in my industry?

It can help businesses in any industry and any size extract the value out of the information available. Data integration could be a basis for a technological innovation such as Machine Learning in Finance.

What are the reasons to implement data integration?

Keeping up with the technological revolution, getting out of the legacy infrastructure, improving data accessibility, improving security, better understanding the value of every piece of information, and many more!

What is the deal with cloud data integration?

Cloud integration can help you unify all resources in your organization, store it in the cloud, and have the opportunity to extract valuable insights.

What are the approaches and strategies to do this?

There are multiple approaches, each one better suited for a particular business case than the other. The most common are manual, middleware, application-based, uniform access, and common storage.

Conclusion

The most important thing about your custom data integration strategy is using it as part of a greater vision. It’s not just a one-time deal, but rather a step in your digital future. Feel free to contact us at SPD Group for a consultation regarding the data integration strategy for your business. We will help you to get out of the legacy infrastructure and make the best out of modern technology and approaches.

Original post by Roman Chuprina. Click here to read.