Few will disagree that businesses operate better and achieve more of their goals when they can use their data strategically. But given how many forms and sources — think CRMs, ERPs, mobile apps, and dozens more — of data exist in today's enterprise, assembling and making use of that information is easier said than done.
For years, companies relied on data warehouses with specific schemas for a particular use or application in the business. Marketing teams, for example, would use data to better understand the success of a particular campaign, get a clearer view into the buyer’s journey, or project the types and quantity of content they’ll need in the future.
However, any time a team wanted to add a new data set for greater context and more source material, it required a lengthy manual process. They’d have to separately define requirements, source new data, and manually build new processes to update the data warehouse — all while making sure that the updated schema did not break existing code.
Fortunately, automated data integration processes can gather structured, unstructured, or semi-structured data from virtually any disparate source into one place. Consolidating data to a central repository enables teams across the organization to improve performance measurement, gain deeper insights and actionable intelligence, and make more informed decisions to support organizational objectives.
A unifying theory and practice
If this seems like something only for the data-heaviest of enterprises, you might be surprised to learn just how top-of-mind data integration is across industries and sectors. In a 2016 Capgemini survey, 65% of business executives said they feared becoming irrelevant or uncompetitive if they failed to embrace big data. In the two years since that survey, that percentage continues to rise as executives across the board realize the negative impact not having a data strategy and solution in place will have on every aspect of their operation.
Remaining competitive — operating more efficiently, cutting costs, and increasing revenues — means finding ways to aggregate, analyze, and mobilize data to the fullest extent of its value. Not as a "someday" goal down the road, but as a driving initiative today.
Data integration works across your organization to support any number and type of queries — from the most granular of questions to the highest overarching concepts. Data integration can be applied to many specific use cases that impact every team and department in your business, including:
Business intelligence - Business intelligence (BI) encompasses everything from reporting to predictive analytics to operations, finance, and management. Further, it relies on data from all over your organization to uncover inefficiencies, gaps in process, missed revenue opportunities, and more. Data integration supplies the BI tools and technologies your company is already using with the data streams your teams need to make their next big strategic decisions.
Customer data analytics - Knowing who your customers are, what behaviors they exhibit, and how likely they are to stay loyal or look elsewhere is paramount to good business. Data integration allows you to pull together information from all your individual customer profiles into one view. From there, you can see what the overall trends are among them, and supplement your existing customer retention strategies with real-world insight.
Data enrichment - Combat data decay by continuously updating names, phone numbers, and emails. Combine these with specific pieces of unique information about each customer to form a much richer and more accurate picture of your buying audience.
Data quality - Ensuring data quality can be a challenge, as it means determining what your data requirements are upfront, how to create them, and the level of tolerance for errors your organization will have — a job few people want. But automating data integration eliminates most of the risk of not complying with your company's data governance policies, increasing both the accuracy and the value of the information available to teams across the organization.
Real-time information delivery - Businesses cannot wait days to crunch numbers; they have hours and sometimes minutes. That's why real-time information delivery becomes crucial for any business to quickly adapt to market, customer, vendor, and even regulatory and compliance changes. Data integration enables you to sample data from any point in the collection process at any time to get minute-by-minute insight into processes, workloads, and interactions.
Next steps: purchasing a modern data integration solution
As business's dependency on a single source of truth grows, so does the need for a modern data integration solution. Cloud-based, automated data integration combines data from all your applications, APIs, and databases and filters it into a single interface so you can query and manipulate it as needed.
Modern data integration uses data pipelines and a variety of integrations to replace outdated traditional methods of manually managing data sets, scrubbing them, and loading them into the individual data lake or warehouse environments. Now, you can store, stream, and deliver the data you need, when you need it, from any centralized data warehouse — Amazon Redshift, Snowflake, Google BigQuery, Azure, or a number of other options.
A data integration solution like Alooma offers a simplified and secure method of data collection, combining all your current data silos into one location that easily scales with your business needs. Your data is your own and automating data integration processes allows you to define data types and destinations, enrich data in the stream, catch errors and anomalies, and get real-time insight into events as they're happening — all with a few clicks.
Contact Alooma today to learn more about how a data integration solution can benefit your business.