Enterprises are awash in data, and the number of sources of that data is only increasing. For some of the larger companies, data sources can rise into the thousands – from databases, files and tables to ERP and CRM programs – and the data itself can come in different formats, making it difficult to bring together and integrate into a unified pool. This can create a variety of challenges for businesses in everything from securing the data they have to analyzing it.
What is Data Integration?
Data integration is the process of combining data from different sources to help data managers and executives analyze it and make smarter business decisions. This process involves a person or system locating, retrieving, cleaning, and presenting the data.
Data managers and/or analysts can run queries against this merged data to discover business intelligence insights. With so many potential benefits, businesses need to take the time to align their goals with the right approach.
Many businesses keep their data in silos and employ analytics at a process or departmental level. Centralizing these data silos to create a data mart, warehouse, or lake gives organizations more visibility over operations and results in more accurate analytics that take a wider range of internal and external factors into consideration.
Among other things, centralizing data helps organizations to:
- Gain a global vision of their customers which enables them to understand how their customers interact with different areas of the company, including sales, marketing and customer service;
- Empower analytics to achieve a 360-degree customer view with in-depth customer insights across all channels to better understand each customer’s value, their product and service interests, and how they prefer to interact and be served by the organization; and
- Determine customer or account level profitability. We have seen this metric used to help organizations make key decisions like call center routing, marketing and solicitation, and risk mitigation.
Why Integrating Data is Essential to Technical and Business Practices
1. Every data type has its strengths
This dataset is the result of integrated raster and point cloud information, and offers the best of both worlds.
Every data format was designed for a reason. Each one represents information in a way no other format can, with unique attributes, metadata, structure, and schema. Integrating data from different formats adds various levels of specialty to the dataset.
2. Take advantage of specialized applications
Similarly, every application was designed for a reason. That is to say, every piece of software that works with data represents, analyzes, and transforms information in a specialized way. By integrating data into a format accepted by that application, you’re giving yourself the power to open and use your data in that software.
3. Reduce data complexity
A data integration solution simplifies the interaction between diverse systems. Forming a data integration plan, on the other hand, is like entering that web with a machete. Data integration is about managing complexity, streamlining these connections, and making it easy to deliver data to any system. This might involve creating a data hub that’s easy to publish to and subscribe to.
4. Increase the value of data through unified systems
Bringing disparate datasets together increases the value of the information. Examples include:
- merging with and leveraging external data (e.g. from vendors);
- combining data of varying natures (structured, unstructured, spatial, tabular, web, raster, big data, etc.);
- applying spatial information to non-spatial data;
- combining databases from different repositories; and
- creating a uniform schema for a group of datasets without metadata standards.
5. Make data more available
Centralizing your data makes it easy for anyone at your company (or outside of your company, depending on your goals) to retrieve, inspect, and analyze it.
Easily accessible data means easily transformed data. People will be more likely to integrate the data into their projects, share the results, and keep the data up to date. This cycle of available data is key for innovation and knowledge-sharing.
6. Easy data collaboration
Data integration makes it easier to collaborate on potentially overwhelming information.
With accessibility comes easier collaboration. Anyone who works with your data will find it easier to use brain power now that they can actually use the data in the format they require. Whether collaboration involves sharing among internal teams and applications, or across organizations, integrated data is more complete because it has more contributors.
7. Understanding data means smarter business decisions
Integrated data means transparent processes within your company. By giving people the flexibility to use your data in whatever system, you’re giving them the opportunity to better understand the information. It’s much easier – and more informative – to navigate through organized repositories that contain a variety of integrated datasets.
Applying location intelligence to your dataset, for instance, makes it spatially comprehensive and offers new levels of insight around that dataset, which leads to better decision-making.
Integrating with other data types can also mean conforming to interoperability standards to save on business costs. Further, open source data formats offer many advantages for businesses.
8. Data integrity
Data integration technology should cleanse and validate the information passing through. Obviously, we all want our data to be robust and high quality. An integration strategy ensures data is free of errors, inconsistencies, and duplication.
9. Make your data live
Integrating with cloud systems is one way of enjoying the benefits of live data.
An integrated data solution makes it easy to keep information up to date. One input can propagate across all integrated systems, keeping your data current. In fact, your data can even be real-time if a server or cloud solution is part of the integration strategy.
Even if data doesn’t need to be accessed regularly, siloed data is still inefficient to work with, impossible to collaborate on, and runs a high risk of conflicting with external data. By actively integrating your data, you avoid the dreaded silo and gain the boundless potential outlined above.
Any data type can live in a wide variety of sources. Developing an integration strategy—both the technical and business aspects—is critical to ensuring your organization’s data reaches its maximum potential.
The Litcom Approach
Litcom’s systems integration experts help clients drive business and technical results from their IT stacks. We first start by aligning with clients on their desired business outcomes and KPIs, establishing an agreed upon reference architecture and roadmap for implementation. From there we work together to prioritize and execute integration projects, further building out to accommodate scaling needs for the enterprise. Contact us today for more information.
