It’s been more than a year since CDW first published the “Smart Data for Finance” white paper, and much has changed in the industry and at CDW. We’ve broadened our analytics practice to cover many different industries and brought in subject matter experts who can tailor analytics solutions to the needs of many diverse businesses.
At the same time, the world of analytics has evolved significantly, and we’re seeing new trends that will shape the way that businesses use their data in the years ahead. I’d like to take a look at three specific trends that will change the way we work with data over the next 18-24 months.
Prediction 1: Natural Language Querying Will Become Widespread
We’re already seeing natural language querying capabilities integrated with the analytics tools that we use every day. This technology allows nontechnical users to ask ad hoc questions about their businesses without learning Structured Query Language (SQL), R or another programming language. This capability will transform the way data is integrated into a business by breaking down access barriers that have persisted for decades.
Imagine a district manager for a large retail chain who oversees dozens of stores. If a trend breaks out on social media, such as interest in a particular pair of sneakers, the manager can quickly ask, “How many shoes are in stock in each store in my region?” and receive a response without waiting for someone to translate it into a SQL query. This facilitates rapidly shifting inventory between stores to capitalize on the opportunity.
Prediction 2: Organizations Will Find Practical Uses for Quantum Computing
We’ve heard about the advent of quantum computing for quite some time, but I believe we’ll see our first practical applications of the technology over the next two years. General-purpose quantum computing is still far off in the distance, but we will likely see specialized applications of quantum subroutines in the very near future. This will unlock a new era of massively parallel computing and empower organizations to take advantage of vast stores of data.
I’m particularly excited about the applications of quantum computing in healthcare. Imagine a patient walking into a doctor’s office and handing the nurse a smartwatch that has been measuring health data for weeks. The nurse can read the data off the watch and quickly learn the patient is at high risk for hypertension and advise the doctor that a preventive prescription is in order. That’s a dramatic shift in healthcare from the traditional reactive approach, enabling medical professionals to take a proactive approach that addresses underlying issues before symptoms arise.
Prediction 3: Orchestration Tools Will Continue to Mature
The foundation of any analytics program is the computing power that supports the development and application of data-driven models. Until recently, we’ve been forced to choose between deploying our analytics applications in the public cloud, in private clouds or in traditional on-premises data centers. Despite desires for portable workloads, we lacked the practical tools required to easily shift workloads between different deployment models. Containerized computing changes all of that, making workloads truly platform agnostic.
One of my clients in the financial services industry is already using powerful orchestration tools to manage thousands of workloads across more than a hundred different cloud platforms. If a data center in Iceland suddenly offers excess computing power at a significant discount, my customer can automatically deploy batch workloads there to take advantage of the cost difference. That rapid response improves the efficiency and effectiveness of analytic computing.
As you work to mature your own organization’s analytics practices, these predictions can help shape the way that you plan your future work. CDW stands ready to assist with an array of tools and partners who are familiar with your industry and can guide you along your own analytics journey.
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