By: Praveen Srikantaiah, Blueocean Market Intelligence Sr. Market Research Manager
In 2016, there will be 5.5 million new things connected to each other. By 2020, there will be 20.8 billion connected things, says Gartner.
There is a sudden increase in the amount of data being generated everyday by people, machines, and things. All of this data, when collected, stored and analyzed can reveal valuable insights for companies. For example, a Boeing 737’s engine generates 10 terabytes of information during a 30-minute flight. Presently, this vast amount of information goes unattended. What if companies could harness this information in real-time? Imagine the kind of insights they would have access to. It could help the ground control center take corrective actions in time, saving both lives and assets worth millions.
In a smart home, devices are connected to each other and can communicate. This generates a lot of data that should be managed well for the entire system to function effectively. This same data can also be used by retailers to provide services like groceries, refills, and so on to create a seamless flow of information between systems and security. In farming, John Deere is using internet of things (IoT) installed in farm machineries to provide farmers with information related to crops and best practices in farming. In short, they are now also selling data besides tractors. According to a report by McKinsey, the IoT business will deliver $6.2 trillion of revenue by 2025.
The challenge lies in harnessing — storing, managing, analyzing, and synthesizing — this enormous amount of unstructured data that will only grow every day. According to an IDC report, by 2019, service providers will have to increase datacenter capacities by 750 percent, thanks to IoT. Do organizations have the bandwidth to handle unstructured data at that scale? What about storage? How do we manage the unstructured data that is coming in at such a huge volume, speed, and variety? Can an organization’s current analytics engine process this quantum of information? These are the questions every organization looking to leverage the power of IoT should think about now.
To understand customers better and gain a competitive advantage, it is important for companies to take charge of their data. The major challenges that companies primarily face are structured around data storage, management and analytics.
Data Storage – SaaS or On-Premise?
A tough question that many face is where to store their data. Is it at the company’s data centers on premise, or on the cloud or a mix of both? Unfortunately, there is no one answer to that question. The answer depends on the company business model, goals around harnessing data for decision-making and industry regulation.
For example, for companies in the healthcare industry, regulation and compliance it may be an issue, but for others in transportation, accessing data real-time and taking action will be crucial.
Regardless of the choice companies make, they must focus on some core areas of concern such as scalability, security, auditability and access of data.
Data Management – Data as a Service?
When “data management” comes to mind, people often think about “database management.” “Database management” deals with managing the data that gets stored in an organization’s systems. “Data management” on the other hand, deals with provisioning data to internal parties such as stakeholders and decision makers.
It is very important for companies to think of “data management” through the lens of the end data “consumer.” Sorting, arranging and categorizing data, and making it consumable to users is an important step that organizations often overlook. If there is a lot of data that is not organized in a specific pattern, sequence or a recognizable format, it is as good as useless. In fact, one can argue that it is a drain on the budget and a waste of money to even collect that data.
Companies must wisely choose who performs this function in the organization and what tools and technologies are to be employed. SaaS tools such as LiNK automate most “data management” steps and allows organizations to harness the power of an integrated view of multiple data sets emanating from a variety of sources.
Once data is stored, organized and made available comes the last but very exciting step in the data lifecycle management.
Historically, organizations have relied on one or two sources of data as “sources of Truth.” In reality, organizations can benefit from having a 360 view of their business by intelligently analyzing an ensemble of data from a variety of sources.
Challenges around data analytics should not only focus on the data sets or tools and techniques organizations should employ. The future will be one where the analytics departments will be forced to be agile and nimble in order to be more predictive, and drive faster and better decision-making.
Blueocean Market Intelligence is a global analytics and insights provider that helps corporations realize a 360-degree view of their customers through data integration and a multi-disciplinary approach that enables sound, data-driven business decision. To learn more, visit www.blueoceanmi.com.