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What to Expect of Big Data in 2015

Big data is going to be a space to watch this year. Here’s what to expect.

1. The Democratization of Big Data Analytics.

Over the past year, there has been incredible growth in the use of cloud-based data analytics services, and the cost-effective nature of the cloud will only accelerate this trend. Even organizations that once thought advanced data analytics were out of their realm of possibility can now begin managing and analyzing both structured as well as unstructured data, quickly and cost-effectively.

Essentially, the cloud will offer a greater array of choices for organizations to hit their desired Big Data benefit/price point trade-off, as well as lower the bar for companies looking to experiment with Big Data, particularly unstructured data.

2. Unstructured Data Grows.

Unstructured data volumes – comprised of things like human information, machine sensor data and Internet of Things (IoT) data – will continue to grow at a mind-boggling rate. According to Gartner, IoT data, excluding PCs, tablets and smartphones, will grow to 26 billion connected devices by 2020.

Organizations will increasingly seek solutions that can tie structured and unstructured data sources together virtually, giving greater context to the structured data that most organizations have come to rely on.

3. Predictive Analytics Becomes the Norm.

Predictive analytics will evolve beyond the next “cool thing,” to a “you better have it or else” type of functionality. Reengineering for Big Data will be critical as business processes must be geared toward action at the speed of insight. There’s no value in identifying what customers are doing every minute of the day if you can’t respond predictively and proactively. By the time you’ve ETL’d (extract, transform and load) the data in some warehouse or Hadoop cluster, it’s too late.

Organizations will re-engineer their Big Data environments to enable information streams, from both within and beyond the enterprise, to be accessed, analyzed and shared in real time. This will be the key to increasing revenue, improving knowledge worker productivity, and lowering costs.

4. Big Data Will Change IT Operations.

Companies who “get” Big Data are going to apply Big Data principles and practices to their internal IT operations first and foremost, long before they’re used for marketing and customers. For years, we’ve heard that “IT is the business.” Increasingly, Big Data will become the basis of competition and growth for individual firms, and the most logical place to exploit Big Data benefits will be an analysis of IT machine data itself – identifying ways to reduce waste and maximize productivity across the IT environment.

Big Data analytics will also play a role in identifying IT security threats, which are constantly growing and evolving.

5. Big Data for Everyone.

Today’s universities can’t seem to train data scientists fast enough for CIOs. Many in the industry view data scientists – those individuals with engineering and business skills, as well as the statistical savviness – as the key to analyzing and deriving value from the Big Data companies generate. But the current lack of so-called “Big Data talent” should not hold businesses up in terms of launching big data initiatives. Rather, the key will be empowering business analysts of today with tools they already know. In fact, the idea of a “Data Scientist” may very well be played out in a couple of years, and the “Data Savvy Business Person” will likely emerge as the new rock star.

However, it’s important to note that, if a company assigns big data to its existing big BI teams, they’re almost guaranteed to fail. The tech, thinking and approaches that lead to success at BI almost guarantee failure at a Big Data. It takes a whole new approach.

In addition, the availability of data analytics in the cloud presents a huge opportunity for developers, and we expect the big data developer community to increasingly emerge as a hotbed of innovation. Cloud-based Big Data services represent decades of significant intellectual property around managing, accessing, and analyzing a wide range of data, including unstructured information that developers can now use like they have used Amazon Web Services or open source systems.

Developers have just begun to exploit the value of Big Data, especially unstructured data, and this trend will only accelerate in the next few years.

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