What is Data Integration and why it’s important?
The process of combining the data from various sources into a single unified perspective is called data integration. Data is undoubtedly one of the most valuable assets of today’s businesses. However, if data is scattered and there is no easy way to analyze accumulated info from different systems, you might be missing important benefits that can make or break your business growth.
Furthermore, the different units in your organization are most likely using various systems to handle daily tasks. For example, your marketing and sales teams might be working with a CRM, where customer data is kept and processed. On the other hand, the service desk team might be using an ITSM system, where service requests and issues are stored. Only sales and marketing work with the CRM and the service desk team works with the ITSM system only as well. There will be cases when other teams will need to access that data. For example, a customer submits a bug/enhancement request in the ITSM system. The Sales team needs to be informed about the inquiry as well as which customer is requesting it. This leads to data being transferred manually, via emails, spreadsheets and phone calls. And when that happens, mistakes are inevitable.
This is why integration is so important. It not only gives you a complete overview of your data, but also helps teams collaborate better, eliminate mistakes and delays, and do more for customers.
With an integration in place, information is transferred seamlessly between systems. The necessary data is there in real-time for the people who need it. Mistakes are brought to a minimum, and customers get quicker resolution to issues.
Data Integration market forecasts
Since systems and their connection are so vital in today’s organizations, the global data integration market is rapidly growing. According to Fortune Business Insights, the market is projected to grow from USD 11.94 billion in 2022 to USD 29.16 billion by 2029, exhibiting a CAGR of 13.6% during the forecast period.
Markets and Markets predicts that the data integration market size is going to grow from USD 11.6 billion in 2021 to USD 19.6 billion by 2026.
Verified Market Research states that Data Integration Market size was valued at USD 9.26 Billion in 2020 and is projected to reach USD 24.3 Billion by 2028, growing at a CAGR of 12.8% from 2021 to 2028.
One more forecast by Research and Markets says that the Global Data Integration Market size is expected to reach $22.1 billion by 2027, rising at a market growth of 10.4% CAGR during the forecast period.
As we can see, the prognoses are more than optimistic. Various factors are expected to drive this trend and expedite the adoption of data integration solutions and services. Lest have a quick look at the major factors:
- Advancement in big data technologies
New technologies and automatization allow expansion in new markets, regions, and areas. However, this also adds new data sources, like new types of financial transactions, CRM systems, Enterprise Resource Planning software, the cloud, etc. The inconsistency of data, coming from these sources, creates silos and gaps. These silos not only prevent businesses from using the full potential of the data they gather, but also make them prone to errors and critical delays. This is why organizations have started recognizing the need for data integration and are already investing in integration solutions.
- Cloud computing technologies and on-cloud data
Many organizations have already shifted to private or public clouds. This allows them to collect data from sources like distributed servers, remote sensors, and the web. Due to the ever-increasing volume of data (including on-cloud data), collected from different sources, most businesses are willing to adopt various strategies so they can maximize the use of that data. Integration tools help them do just that – strengthen the data pool and get valuable insights in real time.
- Inefficiency of traditional data management tools
Organizations require advanced integration tools to be able to manage the complex dependencies created by big data and the ever-growing list of data sources. With AI, learning algorithms, and software development rapidly advancing it is difficult to set standards and catch up with the necessary competence and strategies for handling the newly created volumes of data. Data integration tools must quickly adapt to the needs of enterprises and allow them to combine cloud and on-premise sources and get valuable insights in real time. Integration platforms need to be reliable, secure, and flexible. Businesses will be looking for such platforms to replace their outdated data management tools. An integration platform, able to combine cloud and on-premise sources, that meets all the requirements for flexibility, ease of use and security is ZigiOps. You can start a free trial here.
- COVID-19 Impact
COVID-19 has affected more or less all business operations and reshaped company processes. It brought various challenges, but also urged digitalization and served as an opportunity to improve business models. Many organizations adopted remote working and lots of activities started happening online. This pushed companies to modify their existing processes and start utilizing data integration much more intensely. The data integration market had significant growth during the pandemic and this trend is ongoing.
- Changing nature of business
Organizations are increasingly acknowledging the value of data integration. The nature of business is changing, all new technologies are rapidly expanding, and data integration is becoming a necessity. But the opposite is also true – data integration itself is changing the nature of businesses and is opening new doors for collaboration, partnerships, and cohesive processes. Integration is enabling new meaningful insights and speeding up the resolution of critical issues. Executives prioritize customer satisfaction, smooth operations, and strategic outcomes, and data integration plays a key role in achieving these goals. This is a major factor for the steady increase of data integration adoption.
Source: Research and Markets
If you have not yet benefitted from data integration in your organization, it’s time to start planning it. Explore smart integrations – book a free demo of ZigiOps integration platform.
Data Integration trends
We have already reviewed the major trends in data and application integration in the beginning of the year. You can check them in this article.
However, besides real-time data analytics, hybrid, no-code and cloud-ready, there are a few trends that are even more forward-looking, and we would like to mention them here.
- AI-enabled data integration
Artificial Intelligence is driving the next generation of data integration solutions. AI helps enterprises automate different data integration stages, like data ingestion, classification, processing, security and transformation. AI-enabled data integration is still a new concept, but data specialists are already leveraging its ability to classify sensitive data, identify duplicates, discover connections within the data and overcome silos.
- Use-case-driven data integration
This approach helps facilitate new and emerging business use cases where data integration is needed. Customers are demanding end-to-end integration solutions for cases like Internet of Things analytics, Customer 360, edge computing and more.
- Data Security
The increasing demand for data security is in parallel with the growing amounts of data that companies need to deal with. Organizations have strict requirements for the security of the platforms they are using, and data integration tools are no exception.
- Data Quality
Data quality is a measure of how accurate, complete, reliable, and suitable data is, depending on its purpose. Modern data integration platforms are incorporating data quality features to help organizations with the challenges of the data exponential growth.
- Data fabric and data mesh
The data mesh architecture provides a decentralized connectivity layer that allows users to access data from different sources and locations. This way they can access and query data directly, without first transporting it to a data lake or a data warehouse. The quick access enables real-time analytics and sets time-to-value to a minimum. Data fabric is an integration approach that uses an architecture and services (running on that architecture) that help organizations orchestrate data across hybrid multi-cloud environments. These approaches are very powerful, as they standardize data management and practices across cloud, on premises and edge devices.
Data integration helps organize and simplify different processes in companies. It saves time and increases productivity. The data integration market is steadily growing, driven by big data, cloud technologies and the requirements for faster analysis, and lower time-to-insights.
Businesses are slowly starting to realize that the pace of development of technologies and the evolution of data sources, makes data integration a must.
On the other hand, the majority of data integration tools are not yet mature enough to meet the challenges that the rising technologies set. They need to be faster, more secure, cloud-ready, and at the same time flexible and able to serve complex use cases.
There is a number of new approaches that are just starting to rise in the world of data. The Data mesh, based on microservices and serverless architectures, Data Fabric contributing to AI-enabled integrations, use-case-driven integrations that specialize in complex connections between various sources of data. There is a lot to see in the coming years, but the time to start thinking about integrating your data is now.
A no-code integration platform that allows flexible data mappings and is easy to use even without technical background can help you reap the benefits of connecting your systems. With ZigiOps you can integrate your monitoring, CRM, ITSM, DevOps and other systems in minutes without writing a single line of code. Book your free demo here.