Big data analytics offers powerful discovery tools for enterprises seeking to derive meaningful insights from data. While insights are great, generating right insights that power business decisions are what matters today. And when we talk about insights, it is impossible to overlook the importance of visualization. Data visualization has become an indispensable part of businesses worldwide and an ever-increasing part of our daily life. In an exclusive interaction with Analytics Insight, Josh Parenteau, Director of Market Intelligence at Tableau, explains how Tableau has changed the market dynamics of big data analytics and how it empowers organizations and business users to make better decisions and transform the way they work.

Analytics Insight: Kindly brief us about Tableau, its specialization and the services that the company offers.

Josh: Tableau is the leading provider of visual analytics solutions, with more than 70,000 users worldwide. The company was founded to help people in all industries see and understand their data, from global enterprises like PepsiCo and VISA, to early-stage startups and small businesses. Our platform is designed from the ground up to make data analysis easy and second-nature for our users, with no coding required.

Analytics Insight: Tell us how Tableau is contributing to the Big Data Analytics industry globally and how the company is benefiting the clients.   

Josh: With the massive amounts of data being generated and collected by modern organizations, business leaders want to make sure that they're making the most of this asset. By adopting analytics tools such as Tableau, these companies are seeing an immense return on their investment through the identification of new revenue opportunities, operational inefficiencies, or underutilized resources that can be taken advantage of.

Kindly share your point of view on the current scenario of the Big Data Analytics and its future.

Josh: Data analytics is no longer the domain of the data analyst or IT expert. Previous analytics and visualization tools would require technical and industry expertise, or even advanced coding to build effective dashboards and visualizations that accurately convey data. Modern visualization tools like Tableau let anyone in the business, at any skill level, uncover valuable insights from the data that they're using every day.

Analytics Insight: How are disruptive technologies like big data analytics/AI/Machine Learning impacting today's innovation?

Josh: The biggest trend impacting data visualization and analytics innovation today is the prevalence of artificial intelligence (AI) and machine learning. While it may sound scary to IT departments and analysts who are hesitant to relinquish human control, analytic platforms that include AI and ML capabilities are actually going to serve as a highly effective assistant to modern analysts. While there might be concern over being replaced, machine learning will actually supercharge analysts and make them more efficient, more precise, and more impactful to the business. Instead of fearing machine learning technology, embrace the opportunities it presents.

Analytics Insight: The industry is seeing a rising importance of business and technology enablers like virtualization, convergence and cloud. How do you see these emerging technologies impact the business sector?

Josh: In today's business environment, it's incredibly rare for an organization to maintain their valuable data entirely on-premises or entirely in a cloud storage solution. Any analytics platform should offer flexible deployment options (e.g. SaaS, public/private cloud deployment, on-premises, etc.), and flexible data storage options (e.g. in-DB vs. platform storage (in-memory)).  The platform should also allow for hybrid deployments and the ability to change deployment options over time with little or no impact to end-users.

Analytics Insight: How is Tableau helping customers deliver relevant business outcomes through the adoption of the company's technology innovations?

Josh: The Human Resources team at Wells Fargo uses real-time reporting to deliver, track and train 130,000 employees while managing millions of hours of training materials across multiple divisions. They also use Tableau within the customer insights team, who use Tableau analytics in order to redesign the company's business banking portal. Using the platform, they were able to use a small team to make a big impact on the redesign. They were able to focus on analyzing data that told the collective story of their customers, and ultimately achieved desired results for their new banking portal.

Lenovo is another great example. With Tableau, their Analytics BI & Visualization team created a flexible sales dashboard that departments can adapt for ad-hoc analyses, leading to a 95% improvement in efficiency across 28 countries. The e-commerce teams analyze customer engagement metrics to craft a better online experience—leading to better brand perception and increased revenue. Human resources consolidated 100+ static reports into a set of strategic dashboards, encouraging a data-driven approach to reach team milestones.

Analytics Insight: What is the reason that organizations are using analytics/big data/AI/ML/Big Data Analytics? 

Josh: The hype and excitement surrounding AI, which encompasses machine learning (ML) and deep learning, has surpassed that of big data in today's market. The notion of AI completely replacing and automating manual analytical tasks done by humans today is far from application to most real-world use cases. In fact, full automation of analytical workflows should not even be considered the final goal — now or in the future.

In fact, the term assistive intelligence is a more appropriate phrase for the AI acronym, and is far more palatable for analysts who view automation as a threat. This concept of assistive intelligence, where analyst or business user skills are augmented by embedded advanced analytic capabilities and machine learning algorithms, is being adopted by a growing number of organizations in the market today. The utility of these types of smart capabilities has proven useful in assisting with data preparation and integration, as well as analytical processes such as the detection of patterns, correlations, outliers and anomalies in data.

Analytics Insight: How does Tableau's strategy facilitate the transformation of an enterprise?        

Josh: Tableau helps people see and understand data. Data can empower a deeper understanding of the business to help strategic leaders more accurately assess requirements, risk, and ROI of large-scale projects. Simultaneously, greater clarity into the nuances of the organization's challenges enables a more targeted, data-driven approach to addressing the needs of the business, meaning strategic initiatives are less of a gamble. Tableau enables organizations of all sizes to put actionable insights into the hands of the decision-makers, rather than an isolated data science team, leading to faster and better outcomes.

Analytics Insight: Could you highlight Tableau's recent innovations in the AI/ML/Analytics space?

Josh: We recently just launched Tableau Prep, a new data preparation and transformation tool that empowers more people to get to analysis faster by helping them quickly and confidently combine, shape, and clean their data.

A recent Harvard Business Review article reports that people spend 80 percent of their time cleaning and shaping data, and only 20 percent of their time analyzing it. People can't easily analyze large chunks of their data because it is in the wrong format or comes from various sources. But getting that data ready to analyze can be quite difficult, with today's data prep tools often requiring specialized coding skills.

Tableau Prep has customized visual experiences that make those complex tasks – such as joins, unions, pivots and aggregations – simple. It is a drag and drop experience, with no coding or scripting required. In addition, it's seamlessly integrated with the Tableau analytical workflow, making it easy for people to get insights from their data faster.