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@BluePatagon Entrevista con Anand Ekambaram, Country Manager India en Tableau Software.(Ingles)

Interview With Anand Ekambaram, Country Manager India At Tableau Software.

Analytics India Magazine interacted with Anand Ekambaram, Country Manager India at Tableau Software this week. He shared his thoughts on the recently-launched Tableau Prep, various trends in business analytics, growth plan for Tableau in 2018, and much more.

Ekambaram, who is a strategic thinker and business leader has gathered extensive expertise over the years in managing organisations and business units, with a focus on driving profitable growth.
With over 20 years of leadership and management experience across diverse geographies and industries such as education, technology, enterprise software and others, he has worked with teams to deliver solutions that create customer value. A graduate from BITS Pilani who also has an MBA from the Nottingham University Business School, Ekambaram is focussed on driving innovations for the Tableau.
Analytics India Magazine: How does the recently-announced Tableau Prep stand out? How do you compare it to your other products like Tableau Desktop, Tableau Server or Tableau Online?
Anand Ekambaram: Tableau Prep is an entirely different product from Tableau Desktop, Server and Online.
All the products that we have launched so far, have a different purpose to serve. With Tableau Desktop the idea was to enable our customers to quickly and easily buildpowerful calculations from existing data, by just dragging and dropping it, making the entire journey simple, efficient and quick. Tableau Server helped bring these capabilities to the enterprise. When we realised that cloud was going to be the future and there was a need to move to the cloud, we launched Tableau Online.
Similarly, through Tableau Prep, we are addressing the problem of customers not being able to readily analyse much of their data because it is either in the wrong shape or in disparate sources. Consequently, getting data in a useful form won’t be a complicated and time-consuming process anymore and, it wouldn’t require any specialised skills. A recent HBR study says people spend 80 percent of their time prepping data, and only 20 percent of their time analysing it.
We are broadening our platform and introducing offerings that are tailored to meet the unique needs of users from the individual analyst to everyone across an organisation. Data prep is an entirely new space for us and it gives us a chance to launch a new product in a new space which has the opportunity to be democratised.
AIM: As data preparation remains a key challenge across the world, how do you aim to resolve this using Prep?
AE: With Tableau Prep we intend to do for data preparation what Tableau did for business intelligence. Data preparation has always been a specialised, labour-intensive task. But not anymore. Tableau Prep will take an otherwise painstaking task and make it easy, visual, and direct. It would empower more people to analyse faster; hence helping them quickly and confidently combine, shape, and clean their data. It employs smart algorithms, making data prep easier and faster.
We’re making data prep approachable for more people through a visual, flexible and direct experience that provides immediate results. Users are able to combine, filter, aggregate, clean and reshape their data — all by just pointing and clicking. Tableau Prep shows data visually with three coordinated views letting users see row-level data, profiles of each column, and the entire data preparation process.
Eventually, we want to make it stress-free for more people to have access to the most powerful analytics platform on the market, irrespective of their specific needs or skill sets.
AIM: How do you integrate Prep with other products?  
AE: We’re on a journey to become an end-to-end analytics platform which can be deployed broadly and easily at scale. For the same reasons Tableau Prep is enabled with capabilities that allows it to be directly integrated with Tableau Server and Desktop.
Tableau Prep is available through our Tableau Creator subscription, providing the full power of the Tableau platform to users. This enables organisations to empower their entire workforce with Tableau with the right level of capabilities to meet each unique user need.
AIM: Please elaborate on the new subscription offerings by Tableau and how it provides a seamless individual experience when it comes to data analytics.
AE: We must realise that not everyone uses data the same way. A whole segment of people do advanced analysis, mash-up multiple data sources, and create complex data models for the organisations. Others have simple business questions they want to understand through the data they have. Right now, there’s a large, underserved group of people that simply need to consume data in an interactive way to make decisions. They may not need sophisticated analytics to make data-driven decisions.
That’s why we have made our subscription model easier. Now we’re making it easier to scale Tableau to everyone across an organisation. We are tailoring our subscription offerings because different people have different needs within an organisation. For analytics to be pervasive and ubiquitous, we need to make it easy to get data to everyone in every use case. Ultimately, we want to make it easier for more people to have access to the most powerful analytics platform in the market, regardless of their specific needs or skill sets.
AIM: Is migration possible from Tableau Server and Desktop through these offerings?
AE: The existing customer can continue to purchase our products the way that they did in the past. They are not required to move to the new subscription offerings. However, we do believe that subscription offerings provide more flexibility for our customers and we are delivering additional value in these offerings. For our existing customers, we have conversion frameworks in place, to help customers migrate to our new subscription offerings. The core strategy behind moving to a subscription-based model is to align with our customers’ various Tableau needs, lowering their risk and making it easier to scale with their needs.
AIM: Please tell us about the in-memory data engine, Hyper. How do you aim to revolutionise the way data-driven decisions are made?
AE: The world is creating more data than ever before and existing technologies are breaking under the weight of all that data. A great example of this is the amount of data being created by sensors and IoT, and the need to analyse it before it becomes obsolete. So for that very reason we have replaced the core engine of Tableau with Hyper and our customers are already seeing the benefits from day one via a simple software upgrade.
Hyper allows more organisations to make data more useful at all levels. On average we’re seeing a 5x faster query speed and up to 3x faster extract creation speed. We’re talking about turning hours of processing into minutes! Hyper will be embedded into the core of all of Tableau’s products. It will let our customers bring in data faster, query data faster, and analyse fresher data, faster. This is an entirely new architecture that eliminates the need for the trade-off that customers have to make right now — do you want fast performance or fresh data? Hyper eliminates having to choose by enabling customers to add new data as fast as they’re querying it.
AIM: What are the focus areas for Tableau in 2018?
AE: For Tableau, there are two major focus areas:
  • Relentless attention to what our customers and partners need and want
  • Continuous innovation to stay ahead of the curve
We’ve been focused on what our customers and partners need, and we will continue to do that. We are constantly innovating and expanding our analytics platform to serve customers from end-to-end of the analytics flow. By introducing innovative technologies like VizQL, the Tableau Data Engine and most recently Hyper, and Tableau Prep we have revolutionised the analytics market. And our commitment to R&D is unparalleled in the space, greater than 20 percent of revenue since our inception.
Tableau is also incorporating ‘smart’ technologies like machine learning and natural language processing (NLP) into the core product experience. From an ML perspective, we added ‘recommendations’ to Tableau this past year. The idea is applying ML and statistical methods to enhance customer experience through suggested content and analysis — similar to how you get recommendations on Netflix. This allows you to leverage the work of others, work faster and smarter.
Moreover, we acquired ClearGraph this past summer, a cutting-edge startup that enables smart data discovery and data analysis through natural language query technology. Acquiring ClearGraph has helped us accelerate our efforts to bring NLP to our products. This is the next leap in Tableau’s mission to help people see and understand data requires enabling a broader base of data-curious knowledge workers, which includes delivering new ways of interaction that help more people work with data naturally.
AIM: Please tell us about a use case on how various industries are benefited by Tableau’s analytics services
AE: We’re seeing many industries with interesting uses of analytics — from BFSI and manufacturing to tech startups. They have a high value for analytics and we are driving success here. Marico, which is one of the leading consumer products brands in Indiawas facing issues with mining and analysing small and big data to help improve its bottom line. This included getting answers to critical business questions faster, gaining insight into customer data and identifying areas for cost-cutting, and so on, thereby enhancing efficiency and improving the bottom line. With the deployment of Tableau, Marico has standardised data-driven reports and customised dashboards with vizzes reflecting all manner of KPIs for managers to get the insights they need out of the data. Marico business managers now save about 5 to 20 man-hours per month, per analytical report.
AIM: How is the market for business intelligence and analytics in India shaping up? What are the upcoming trends in business intelligence?
AE: As we know now data is the new oil, not only for global enterprises but also for budding startups. Data and its volume is triggering organisations to deploy BI solutions that will elevate and accelerate data-driven decisions. Successful organisations are prioritising a modern BI approach, and in turn, priming their workforce to be analytically savvy. For a competitive edge in 2018, organisations must recognise the strategies, technologies, and business roles that can enhance their approach to business intelligence.
In addition, popular culture is fuelling a dystopian view of what AI can do. But while research and technology continue to improve, ML is rapidly becoming a valuable supplement for the analyst, providing assistance and driving efficiency. The role of ML to aid an analyst is undeniable, but it’s critical to recognise that it should be embraced when there are clearly defined outcomes. While there might be concern over being replaced, ML will supercharge analysts and make them more precise and impactful to the business.
NLP will empower people to ask more nuanced questions of data and receive relevant answers which will lead to better insights and decisions. Simultaneously, developers and engineers will make greater strides in exploring how people use NLP by examining how people ask questions — from instant gratification to exploration. The biggest gain in analytics will come from tackling this ambiguity and understanding the diverse workflows that NLP can augment. The opportunity will arise not from placing NLP in every situation, but making it available in the right workflows so it becomes a second nature to those using it.






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