Drawing clearer insights from the cloud
Many companies are finding an outsized return on their technology investment in a familiar place: their data. That's because the increasing sophistication of cloud analytics is helping more companies unlock value from their information. It’s a trend that’s pushing revenue in the big data and business analytics sector to nearly $275 billion in 2022, according to Statista.
While that number is impressive, the return on investment to organizations that leverage cloud analytics correctly is incalculably greater. Properly specified and executed, cloud analytics platforms can gather, process and analyze enormous quantities of data with ever-increasing speed and efficiency, helping organizations gather in-depth insights on every aspect of their operations.
So with all that cloud analytics can offer, why aren’t more companies taking advantage of these capabilities? And why are some companies struggling to manage it fully and effectively? The answers have varying degrees of clarity, depending on how you look at them.
Blinded by What’s Familiar
One key reason organizations may miss the opportunities and efficiencies of cloud analytics is a reluctance to review the strategy of their data infrastructure and planning. These companies often have systems and resources that were implemented based on imperatives, needs and technologies that may not align with today’s business realities.
In addition, many IT departments suffer from a collection of tools -- once-shiny objects -- in which stakeholders invested significant dollars. When data management and analytics move to the cloud, these tools and the business outcomes they influence need to align with the strategy.
Ironically, some organizations may miss out on cloud analytics because they’re cloud veterans and haven’t revisited its ever-changing features and capabilities. It can be difficult even for those IT professionals advocating for cloud analytics to see a clear path to leveraging its potential within their existing ecosystems.
Case Study: A Full Menu of Insights
Datavail helped a large, quick-serve restaurant firm overcome several challenges in integrating cloud analytics across its global footprint. The firm has a long-standing relationship with Datavail, and we've done significant modernization work on the client's data movement architecture.
To help the client fully use the cloud analytics available, we first worked to corral the sheer volume of data streaming toward the company every minute. Previously, raw, unfettered data was being funneled, though not necessarily refined, through a series of states, places and events.
Many downstream consumers wanted the data in a more consumable format. We developed a process that deconstructs data to an elemental level so it can be reconstructed to the formats that make the most sense for modern consumption by the business users. The process is an on-demand data ordering function, allowing users to pinpoint the information needed, where it emanates from, and the completeness and timeliness of the selection.
Users can now have data provisioned or curated ad hoc without interrupting its traditional flow into the data warehouse. They can use the data to gain quick insight into what happened last quarter, last week, last night or pivot to see the data in near time. The company currently has a clearly and rigorously standardized and maintained structure for receiving timely data and automating its collection, validation and categorization. This framework lets the client quickly pinpoint opportunities and issues and act accordingly.
Robust Analytics Need Quality Data
Of course, even the most sophisticated cloud analytics tool is only as good as the data it’s given. When imprecisions creep into data, for example, lack of freshness or incompleteness, they can lead to incorrect assumptions, like making the right decision for the wrong question or developing solutions for problems that don’t exist.
In working with our restaurant client, we looked at a pilot sampling of locations and began to spot patterns in data quality, such as late store reporting and mislabeled or improperly geotagged stores. The service team developed solutions to refine and remediate data. These solutions could then scale across the enterprise. We also began to qualify the data flow to alert the client to which data was high quality versus sets needing additional refinement.
Unlocking the Potential of AWS
Many companies seeking cloud analytics and business intelligence use Amazon Web Services (AWS). Our client was already using several AWS products, providing a critical advantage that we leveraged throughout the engagement. The platform offers a scalable, comprehensive array of technology services, including on-demand computing, data integration, storage, and data warehousing. Its analytics and data lake services offer speed, which is essential given the short shelf life of many types of business data.
While AWS offers competitive value, solutions spun off from it can become costly due to high volumes. We successfully addressed AWS's high-volume, high-cost dynamic by developing tools that track and measure data consumption. With this data and highly accurate computing and storage estimates, clients can make informed, budget-conscious decisions about the resources they need.
Finding Untapped Value in Data
In many respects, data is the newest natural resource. Like the air and water it emulates, data can provide life and energy and, when amassed, packs tremendous power. It can also become polluted, dangerous or scarce.
From mom-and-pop businesses on Main Street to global conglomerates to local governments and sovereign states, many organizations collect and possess a rich array of data that’s being underleveraged, undervalued or only selectively evaluated.
Organizations turning to cloud analytics and platforms like AWS are poised to gain a competitive and operational edge. Smarter decisions, better service, increased sales and reduced risk are just some of the positive outcomes below the surface of the data. It's time to unlock that value and see cloud analytics for all it’s worth. You may be surprised at what you find.
Jeff Schodowski is the global director of analytics at Datavail. He is an accomplished business leader with 20 years of experience leveraging data and analytics to deliver digital solutions. His specialties include data strategy, project governance, architecture modernization, and more.