Bigger isn’t Better – Solving the Data Dilemma in Four Steps

Today, almost every facet of our behavior, virtual and in-person, can be tracked—from our social media activity to our shopping patterns. Our digital footprints can be followed out into the real world and then back online, and our physical world is being outfitted with sensors in everything from our appliances to the storefronts we pass.

All this data has created an unprecedented commercial opportunity. But, it has also created big problems for businesses. Organizations are pivoting from optimizing scarce resources to ‘harnessing abundance,’ leveraging new technologies to gather geopbytes of data about customers, operations and competitors. However, having more data is essentially useless for businesses that don’t take the necessary steps to harness this abundance. Here’s how companies can survive and thrive in this new era:

Face reality: Datasets need to be consolidated

Most organizations in Canada are struggling with clunky data sets that don’t speak to each other. Before they can unlock the strength of their data, they first need to consolidate it—an essential prerequisite to any digital transformation. And with legacy systems and aging IT infrastructure, it’s no easy task.

Chief data officers–charged with making sense of existing and new streams of information–are facing a messy reality. They are seeing that when it comes to data, bigger isn’t always better. Most established companies currently have their data sitting in a complex network of databases, from mainframes to enterprise data warehouses, which can be very challenging to centralize.

Prescribe change: Lines of business must connect

Different lines of business need to work together to standardize an organization’s data. In addition to collaboration, the exercise requires a high level of technical expertise. Tools need to be identified, and in some cases built, to allow for all this disparate data to be extracted and gathered in one place. Having a dedicated central team to direct this herculean effort is imperative. The right partners can help businesses avoid months of delays and wasted resources.

In more heavily regulated sectors such as banking, the need to understand the origins of increasing sources of data can help to secure the capital needed to consolidate everything. Furthermore, compliance measures may support the modernization of ailing frameworks and spur innovation.

Strategize: Align efforts with business objectives

Without specific goals outlined by leadership, it is not easy for data scientists to identify the hidden patterns that turn big data into meaningful and actionable insights.

Even enterprises that have successfully amalgamated scattered sets of data sometimes find the outcome disappointing. This may be a function of technical challenges returning inaccurate information or simply a case of missing business objectives.

To streamline operations and identify new revenue streams, companies must align on a shared vision for the application of big data. Without this shared vision, your data lake will quickly turn into a money pit.

Execute: Leverage the right tools

If a company is hoping to derive any value from its data, employees must be empowered to use it. Therefore, leaders must take the time to socialize the property across the organization. Clear processes for who can access the data, and how, need to be implemented and communicated.

Visualization tools like Tableau, Qlikview and Vitellus have made data more accessible and readable than ever before. They provide an interactive and visual representation of information, without the need for a computer science or mathematics degree. Thanks to these new tools, almost anyone can use data to illuminate opportunities and drive their business forward. But it all starts with how an organization manages its data.

To make a true digital transformation, companies must become more intelligent, agile, automated, and on the cloud. They need to centralize data, collaborate across the organization to ensure alignment, and strategize to ensure they have the right tools to measure, analyze and take action informed by their customer and internal data. Only then will a business solve its data dilemma and enable exponential growth.

Prashant Juttukonda is the Head of Big Data and Analytics, Canada for Tata Consultancy Services.