The Eight Data Trends To Shape Business In 2017

From Artificial Intelligence, mixed reality and autonomous vehicles to visual analytics there is little doubt that emerging technology will continue to have a seismic impact on the way organisations are structured, managed and run.

Late last year LinkedIn published their annual list of the most sought-after skills employers are looking for in 2017, and it is highly encouraging to see that data analytics takes the spotlight.

Additionally, the Centre for Economics and Business Research (Cebr) reveals the growth in big data analytics and the Internet of Things (IoT) will add an estimated £322 billion to the UK economy by 2020 and create up to 182,000 new jobs.  With this in mind, businesses must ensure they’re keeping up with today’s demands and expectations.

Organisations are already seeing the benefits of these emerging technologies in their business – from increased efficiency to improved return on investment (ROI).  These new technologies are here to stay and in 2017 we expect them to become even more entrenched in businesses, across every sector.

Here are the top eight data analytics trends we see shaping business this year.

1. Customers are at the heart of the business

In a cloud world, software deployments require fewer initial investments of time and money, and customers evaluating software renewals no longer have to worry about large sunk costs. Cloud vendors are focusing on their customers’ long-term success by working in tandem with them to ensure product adoption and business value.

As a priority, they’re offering higher levels of customer support, more robust training resources, and deeper guidance on product adoption, leading to mutually beneficial partnerships. From this, enterprises realise more value from their investments, and vendors are able to build long-term customers rather than one-time buyers.

2. Data moves into the cloud

As businesses continue to move their data to the cloud, the belief that data analytics should do the same is becoming the norm. This year, data gravity – in which all of the data that needs to be correlated for analysis moves to the location of the largest data set – will inspire businesses to install their analytics wherever their data lives.

The cloud has given a boost to data storage, analytics and cooperative working

As such, cloud data warehouses such as Amazon Redshift will continue to be a popular data destination.  While many businesses will continue to deploy a hybrid architecture of cloud and on-premise solutions, cloud analytics will increasingly represent a faster and more scalable solution.

3. Big data doesn’t discriminate

Gartner defines big data as the three Vs: high-volume, high-velocity, high-variety information assets. While all three Vs are growing, variety is becoming the single biggest driver of big-data investments. This trend will continue to grow as firms seek to integrate more sources and focus on the “long tail” of big data. In 2017, analytics platforms will be evaluated based on their ability to provide live direct connectivity to these disparate sources.

4. The rise of a new data hero: IT

For some time now, IT departments have been trapped in the endless churn of building reports to support data requests from the business. Not only does this waste valuable time, but it lacks scalability with the growing data needs of businesses today.  Now, IT is at the helm of the transformation to self-service analytics at scale.

With IT working more closely with the business to ensure a better understanding of data analytics, while also providing governance and security of the data, this will be something that all employees will benefit from.

IT support is back en vogue

5. IT reorients its skill set

Unsurprisingly, continued growth in cloud adoption is creating increased demand for specialist cloud expertise. In response, IT is prioritising specific training on cloud technologies and developing internal training programmes which focus on hosted databases, security, and infrastructure as a service.

IT managers are stepping up their search for candidates with experience in DevOps practices and cloud platforms like AWS, Azure, and Google Cloud Platform. Since concerns like scalability and maintenance are all but taken care of with the cloud, IT departments will place a greater emphasis on agile methods that provide continuous development and delivery of projects.

6. Unlocking more opportunities for IoT

The Internet of Things is producing massive volumes of structured and unstructured data, resulting in an increasing share of this data being deployed on cloud services. While innovations in storage and managed services have sped up the capture process, accessing and understanding the data itself still faces a significant barrier.

Demand is growing for analytical tools that effortlessly connect to and combine a wide variety of cloud-hosted data sources. Such tools enable businesses to explore and visualise any type of data stored anywhere, helping to discover hidden opportunities in their IoT investment.

7. Self-service data prep goes mainstream

Business users need to further reduce the time and complexity of preparing data for analysis. Self-service data prep tools not only allow Hadoop data to be prepped at source but also present the data available as snapshots for faster and easier exploration.

We’ve seen a host of innovation in this space from companies focused on end-user data prep for big data such as Alteryx, Trifacta, and Paxata. These tools are lowering the barriers to entry for late Hadoop adopters and laggards and will continue to gain traction in 2017.

8. Many heads are better than one

In 2017, collaborative analytics will take center stage as governed data becomes more accessible and cloud technology enables easy sharing. This signals the end of an era in which information flowed in one direction. Gone are the days of sharing data via static PDFs or PowerPoint decks, with people sharing live, interactive workbooks and data sources to drive business decisions.

From embedding their dashboards within other enterprise applications so they can reach people where they are, to leveraging the cloud and other sharing functionalities like email alerts and subscriptions for staying in touch are examples of this collaborative nature. Regardless of their role, people will be empowered to wear many hats, from consuming data on dashboards to performing their own ad hoc analysis, to sharing their findings with others.

James Eiloart is SVP Tableau Software EMEA.