The concept of Big Data has been building up for a long time, but we may be close to reaching a pivotal point in terms of its power and impact. Companies are more and more focused on capturing and analyzing every piece of data possible, and as they see return on investment on their Big Data-driven projects, this trend is only going to intensify.

Meanwhile, new hardware and especially software continues to be developed that aids in the collection and analysis of more granular data. The confluence of increased demand for Big Data solutions and the development of tools to provide them is leading to a come renaissance in Big Data.

Data Collection

We live in an increasingly digital world, which means that more and more of our interactions, decisions and actions come at the click of a mouse, keyboard, or a touch on a touchpad. While Big Data isn’t reliant on digitally captured data sources, this is the easiest way to gather raw data.

As such, companies and institutions are able to gather more and more transactional data as to how we live our lives, as well as data on the systems that support us as we do so.

Simply looking at the amount of data being collected, the increase in recent times is staggering. The amount of digital data collected is doubling every two years. That’s effectively exponential growth, and it shows no sign of stopping.

A limitation on the scope and effectiveness of Big Data solutions has always been the completeness and robustness of data sets, and we’re getting more and more complete and all-encompassing data. If nothing else were to change, just the fact that increasing streams of data are flooding in from all sides is helping push Big Data to new levels.

Data Analysis

Of course, collecting data is only part of the battle. In some ways, not even the most significant. It’s easy to become overwhelmed by a massive data set, unable to tease out significance or even know where to look to begin in doing so.

A wide range of software products are being developed to make Big Data analysis more convenient and fruitful. Offerings like Amazon RedShift, which allows for cloud-based storage and analysis of massive data sets, are allowing businesses to better leverage their data. These kinds of applications are creating an environment where we can cut through the chaos of large data sets and extract meaning.

Traditionally, Big Data has been stronger in some business and commerce applications than others. For instance, Big Data has generally been excellent at helping with spending and pricing decisions. However, trying to understand customer motivation and decision-making using Big Data has been something of a mixed bag.

Part of the problem goes back to data collection, as in the past certain parts of the overall data set couldn’t be collected, leading to blind spots that made it hard to see the overall picture. That part of the problem is lessening as data collection becomes more widespread and sophisticated.

But the other part of the issue lies in the analysis. Without knowing what to look for and where to look, Big Data is mostly noise. As time goes on, companies are learning from past efforts and using new, powerful tools to zero in on the type of analysis that produces actionable insight.

Increased Demand for Big Data

Each Big Data success story leads to more businesses and people adopting Big Data approaches to solving problems. These solutions are targeting and increasingly diverse field of markets and scenarios.

The financial industry was one of the early adopters of Big Data, and has seen massive profits from embracing Big Data approaches. Walmart’s vaunted supply chain, which is regarded as its defining competitive advantage, is a study in Big Data applied to business.

Driven by these types of success stories, more and more businesses are beginning to integrate Big Data into their approach to marketing, logistics and design. But it’s not just companies turning to Big Data. The public sector is taking notice as well.

In some cases, Big Data can actually save lives. For instance, governmental disease control and public health agencies are turning to Big Data to track the spread of infectious diseases like Ebola. And national security agencies are using big data to refine security protocols and algorithms to predict and prevent attacks.

The bottom line is that Big Data solutions are getting results, and because of that people are increasingly interested in Big Data. As long as it’s possible to gather data in an intelligible form, chances are that someone is going to be analyzing and using that data in the near future if they already aren’t.

Privacy Concerns

Despite all the positives and success stories regarding Big Data, there are some drawbacks and concerns. On the things companies have to be worried about is public perception of their Big Data strategies. Netflix, a company whose success is partly built on outstanding use of Big Data, faced a backlash over a tweet that pulled the curtain back a little on the scope of their data collection.

People inherently value privacy, and are still somewhat uncomfortable with this Big Data era. The power and profit potential are too high for businesses not to implement Big Data solutions – that genie is out of the bottle and can’t be put back in. However, that doesn’t mean that consumers won’t push back at times. To be successful with Big Data, a business should always be weighing public perception toward the outward face of their collection and analysis.

These same concerns exist between citizens and government. The specter of the surveillance state looks very real when revelations like Edward Snowden’s come to light. As a people, we’re still trying to figure out how to co-exist with businesses and our governments in the context of Big Data.

Despite these concerns, Big Data isn’t going anywhere. Quite the opposite. It will continue to spread in scope and the analysis will get more and more insightful. Smart companies will get on the bandwagon if they’re not already on.

About the Author: Dawn Castell is a loving wife and mother of three and an up-and-coming entrepreneur. With all she has learned about business, she has decided she wants to help other businesses avoid the mistakes she has made and help them succeed even when she is still searching for that very thing for herself. First and foremost is her family. Second is her business and helping others with theirs.