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2016 Trends in Business Intelligence and Data Analysis

By   /  December 3, 2015  /  No Comments

2016 business intelligence x3002016 is about to begin and as we ring in the New Year we’ll be seeing some big changes in the business world. New forms of data analysis will be emerging to offer companies much more by way of Business Intelligence, operational guidance, and strategic market tactics. So what exactly will we see coming into play next year?

More Power and Impact for Data Analysts

One interesting change predicted for 2016 involves the Data Scientist as a “rising star” in many industries. For example, this Harvard Business Review piece calls data scientist “the sexiest job of the 21st century” and talks about how these types of analysts will likely get more clout. Much of this is demand-driven: experts found demand for Python coders increased to the tune of 96% over 2014, and other kinds of increased are planned for roles like Computer Systems Analysts and Information Research Scientists.

Brian Dirking works at Alteryx, a company that helps provide data visualization and data handling services for client companies. Talking about new changes for 2016, Dirking says data analytics people will be more a part of “impactful decisions” and will get more of a seat at the table.

“We’re starting to see greater recognition of data analysts,” Dirking said, using the example of survey results that are improving and saving time in data analytics processes. As tools get better, Dirking said, data analysts can make greater contributions to businesses.

Importance of Location Analytics

Another major driver of business in 2016 will relate to location and geospatial tools that give companies better market intelligence. For example, Dirking talked about “store placement” strategies that can help profits soar.

“This has been a big part of these industries,” he said. His company’s use of drive-time analytics has impressed big companies trying to crunch the numbers on market patterns. He also talked about more granular customer behavior inside a particular physical store.

“How somebody moves through a store, which merchandise they look at, that becomes very powerful,” Dirking said. He also talked about mobile analysis applied in other fields such as sports, and medicine.

Line of Business and IT People Coming Together

People looking at the modern operations of business offices are also seeing a lot of blurring of the boundaries between various types of roles and departments. For example, many expect further integration between IT and “line of business” or relatively un-tech-skilled users, which will make for more seamless processes and open up the use of data analytics to more people.

“As soon as somebody gets an answer, they have another question,” Dirking said, talking about the conventional process that splits IT and line of business into two isolated camps. By opening up the process, he said, companies also improve efficiency and general capability – with the right data in the right hands, people can make better decisions.

Predictive Analytics and Impact on Data Discovery

By collecting more different types of small data pieces, companies will be able to build more elaborate visual models that will help them to act in more precise ways. As an example, Dirking mentioned “market basket analysis” where having better data models shows companies more about what customers are buying, and even what they are most likely to buy in the future.

“It starts to show all sorts of new things that you couldn’t get just by having the data there.” Dirking said. From CRM to sales, predictive analytics and next generation Business Intelligence are set to upset the apple cart in a big way.

Spark Goes Mainstream

Another trend companies like Alteryx are seeing is the replacement of the traditional Apache MapReduce Hadoop system by a new tool, another Apache resource called Spark.

In the old days, a lot of the hardware setups used to read and translate data with physical aggregations of computers with hard disk drives. In that time, it made a lot of sense to use MapReduce to manage all of these scattered physical machines.

Since then, with network virtualization and other advancements, companies have come up with new memory-rich systems that are easier to scale. Dirking says Spark helps to complement these new systems by handling data in more agile ways. In general, we’re expected to see a trend in new data analytics tools that fit a more virtual environment, such as a set of virtual machines or even a container paradigm.

Cloud is Here to Stay

Another prediction that Dirking mentioned is fairly obvious when you look at tech markets. It’s the rise of Cloud Computing, which took off in recent years and still hasn’t stopped. Instead, we’ve seen the splitting of the Cloud field into different types of vendor systems. For instance, a vibrant debate has now sprung up over whether to use private Cloud setups, public Cloud setups, or a combined “hybrid” solution. No matter what companies choose, they all have something in common: they’ve taken the common-sense step of outsourcing a lot of costly hardware maintenance and other responsibilities, to take advantage of the on-demand, scalable systems that Cloud vendors provide. Resources like Ovum’s Cloud Adoption Forecast show majorities of survey respondents reporting their companies are getting on the Cloud bandwagon.

Companies are using Cloud services to host all sorts of powerful data analytics setups. Some, like Salesforce, are centered on Customer Relationship Management. Others are more general. Dirking said Alteryx has seen a lot of customers using things like Amazon Redshift and Microsoft Azure along with Cloud resources that provide scalability and flexible handling for data.

“A lot of this is allowing people to take advantage of faster scaling – but also to access data on mobile devices,” Dirking said.

Along with partners Tableau and Cloudera, Alteryx will host a webinar to go over many of these predictions, explaining to those in attendance how data, a new valuable asset, will become even more useful as the years go on. The event is slated for Thursday, December 10th at 10 a.m. PT.

Specific Use Cases

Some of the above predictive analytics capabilities are going to impact a lot of different markets in very specific ways.

For instance, a recent Alteryx blog post discusses how sports teams such as soccer and rugby teams can use data sets to look at where players are or should be on the field, for new data-driven strategies that are sure to bring a new fan and player experience to many popular sports.

In terms of health care applications, suppose a major company has to deliver an isotope with a very short half-life for cancer treatment. Every day, the company has to think about how much of this research to create, and where and when to deploy it. Before drive-time analytics, there was a lot of inefficiency in routing. Knowing exactly how long it will take to deliver something is going to allow for much greater precision, and save companies and their customers a lot of money time and effort in the future – and it’s a pretty good bet it’ll save lives as well.

Look for these Business Intelligence and data analysis predictions to take shape as 2016 approaches.

 

 

About the author

Justin Stoltzfus writes for Lancaster Newspapers in Lancaster, PA, as well as numerous digital publications like Techopedia, Breaking Modern, IBM Midsize Insider and Toggle. Follow him at Twitter at @SjStoltz or visit his web site at www.local-citizen.com. Stoltzfus is a graduate of James Madison University in Harrisonburg, VA.

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