Tackling the Thorny Problem of Data Integration

Poorly managed data integration projects can have a lasting impact on an organization. Read our tips for ensuring your data integration and migration initiatives go smoothly.

The world runs on big data. Countless organizations were built on data. And yet most companies across industries grapple with one or all of the following: integrating data from multiple sources, managing and analyzing data to drive informed business decisions, and accessing and delivering integrated data across the enterprise. It’s understandable. Integrating, migrating, managing and cleansing unstructured terabytes or petabytes of information is not quick and easy work.

Data and application integration has long been a formidable challenge for organizations of all sizes. Expect that challenge to become more complicated in 2016 and beyond as the demand for readily accessible data, improved business intelligence (BI), and analytics soars to new heights.

According to the results of one survey on the subject of data integration conducted by technology research firm Dimensional Research, 54% of respondents said application and data source integrations is their greatest obstacle. The respondents identified several issues that made the effort onerous including on-premises applications (48%), legacy applications (47%), connectivity (40%), and shared data sources (37%).

Meanwhile, and according to research firm Gartner Inc., there will be more than 20 billion connected online by 2020. The massive volume of real-time data coming from these devices will require a new approach to data management.

Which begs the question: how is your organization accessing, managing, and analyzing and distributing its data? Furthermore, is your company looking at the complete picture by integrating all-important geospatial data or location intelligence into its operations?

Overcoming Data Integration Challenges

With respect to data migration and integration, a successful integration hinges on a number of factors including:

• Setting realistic expectations. Have a thorough understanding of your organization’s challenges, and what the company’s leaders expect to achieve or gain from its data and analysis. Also, ensure your firm’s executives have a clear picture of the amount of work and costs involved in order to meet their objectives. This is the foundation on which your data integration initiatives should be built.
• Dealing with bad or corrupt data. Questionable data quality and the migration of heterogeneous data, particularly from legacy systems, can throw a wrench in your plans. Scrubbing data that is corrupt or incompatible before conversion and migration may take time but it is essential.
• Sufficient storage capacity. When it comes to data warehousing, look long and think ahead. The amount of data your organization will need to collect, analyze and store will grow exponentially year-over-year. Thus, the amount of storage capacity your firm will require now and in the future shouldn’t be given the short shrift. True, data storage can get costly, but the cost of recurring fixes to architectures to address inadequate storage can prove to be far more expensive with time.
• Location accuracy. Collecting location data on your properties enables you to provide an accurate inventory as well as enable spatial analysis of all of your assets. Location-based data insights, whether focused indoor or outdoor, can help your business realize significant cost-savings in numerous ways including increasing worker productivity, ensuring your store or facility becomes more energy-efficient, and optimizing your warehouse and distribution network.
• Adequate budget to integrate and manage data. As mentioned above, your company’s decision-makers need to know all of the costs involved with integrating and then managing corporate data, and allocating the necessary funds to extract, clean, load, and maintain it. It takes extraordinary care and planning to produce a practical and far-sighted budget, but it’s of fundamental importance from the get-go.

As an example of a successful data integration project Spatial DNA had the pleasure to lead on behalf of the Regional Municipality of York, we spearheaded its strategic Open Data Initiative to release information publicly as a means of providing transparency into the government’s operations. We worked closely with York Region to integrate and technologies to enable search and discovery of spatial and other data in a user-friendly way.

Why Location Intelligence Matters

It’s commonly cited that 80% of all data includes some reference to geography. Thus, it is valid for business leaders to weigh to truly understand how it affects business. After all, geography complements BI, and when combined, it provides a more in-depth view of customers and data.

Major BI and database vendors from IBM to Oracle to Microsoft integrate location intelligence with their software platforms. These world-class companies recognize the value of geospatial data and its growing importance to making informed business decisions. Geospatial mapping, data, and capabilities are critical components that should be included in your integration plan in order to attain a holistic view of your data now and in the future.

What data-related challenges is your organization wrestling with? Spatial DNA specializes in helping companies integrate in-depth location intelligence into their enterprise systems, and gain a significant advantage over their competitors. Contact us and let’s get to work solving your data dilemma.