Open Data Science Conference 2018, Boston


We were attending for the second time in the last 3 years the most premier open data conference on the east coast in Boston. Primary reason was to focus on the time series modeling talks by several renowned experts like Jeffrey Yao, AB Wang, Amir Meimand etc. and to also possibly look for possible DS candidates for freelancing/internship for CIEK.

Here is the reason why every data scientist should attend this conference:

• 45 Training Sessions.
• 65 workshops.
• 220 speakers (Yes you read it correctly)
• Around 4700 attendees.

Most of the talks ranged in the areas of deep learning, machine learning, predictive analytics, natural language processing, data visualization & AI research. Common tools used by most data scientists were Python, Jupyter notebooks, R, Julia, Apache Spark and TensorFlow. One of the best talks was given by Cathy O Neil author of Weapons of Math Destruction, delivering a powerful message on how we must be vigilant to ensure data science methods are not used in ways that increase inequality and injustice. Super conference. Marked already for attendance for next year as well.

Applied Machine Learning Conference – Tom Tom Festival, Charlottesville


We had the annual ML conference in our home town Charlottesville, VA. After an astounding success in the first ever major data conference last year, Charlottesville had the honor of again hosting some of the major data & analytics thought leaders in the mid-Atlantic region. The annual Applied Machine Learning Conference convenes researchers, entrepreneurs, and practitioners who use big data and machine learning applications for a day of presentations and flash talks.

At the sold-out 2018 conference, speakers presented findings in everything from “Social Bias in Machine Learning” to “An Introduction to Wikidata”. Particularly entertaining was the advances in graphics computing and image analytics by David Luebke, VP Graphics research from Nvidia.

Data Science Salon, Miami


First stop at a data science conference in 2018. I had come to meet a cruise line client in Miami. Stopped on the way back for half a day at Data Science Salon, Miami. Boutique conference. Interesting talk by Doug Vegas on monetization and productization of data sciences. Key thoughts of that talk:

• Data Sciences teams need to start taking the reins in an organization.
• Data Scientists need to start calling the shots.
• Data Science is a revenue generating function.

Especially like the last point.



In November 2017, New Orleans (Louisiana), hosted the world most important conference on data mining. The 17th edition of this event presented new work on graph analytics, time series patterns and recommender systems, among other disciplines.

The big numbers:

• 778 papers submitted, more than 60% student were first author.
• 72 regular papers accepted (9.3% rate) and 83 short papers. Total 19.9% rate.
• 4 keynotes
• 24 workshops

Overall, we highly recommend attending this conference to anyone dealing with real world data problems, as it helps to get to know the latest results on sophisticated, and efficient large-scale data algorithms.

Interesting readings:


Big data Innovation Summit in Boston

We had a great time at the Big data Innovation Summit in Boston. The main themes of the conference were:

• Customer-Centric Applications of Analytics
• Information Governance to Generate Value & Reduce Risk
• Fostering a Data-Driven Culture
• Implementing a Data Analytics Strategy

There was exciting line-up of speakers from eBay, Etsy, Wayfair, Heineken, NBC Universal, John Hancock, Urban Outfitters, Experian etc. With over 60 senior executive speakers and over 800 participants, there were lots of learnings and networking in the 2 days. Great conference overall as it focuses on use cases of analytics to solve complex organizational problems.


CIEK included in the “Innovators Row” at annual 2017 CBIC gala.

CIEK was selected to be part of the “Innovators Row” at CBIC annual gala ( held on May 10, 2017 in Charlottesville, VA.

The CBIC Awards honors enterprising Central Virginia (VA/DC area) entrepreneurs. CIEK earned a spot on CBIC’s Innovator Row through a competitive jury process. which showcases startup ventures before an audience of the region’s leading technology entrepreneurs, investors, educators, and public officials.


Global Bayesian Conference – Nashville

blog-img-big-12BayesiaLab hosted its global conference of bayesian experts and practioners in Nashville, TN on September 29, 2016

Marketing has always sought those moments, or touch points, when consumers are open to influence. One of the central concepts of marketing and sales is the funnel — through which consumers are supposed to systematically move from awareness through consideration to purchase. Today, the funnel concept fails to capture all the touch points and key buying factors due to the explosion of product choices and digital channels, coupled with the emergence of an increasingly discerning, well-informed consumer. A more sophisticated approach is required to help marketers navigate this environment, which is less linear and more complicated than what the funnel suggests.

Our client – a leading automotive aftermarket retailer had a general idea that their brand purchase funnel was not linear. However, they had never quantified the contribution of various touch points to purchase intent and the interaction between each of its brand drivers. Using Bayesian network modeling technique, we helped the client answer the following essential questions regarding the consumer decision journey:

  • What are the key brand performance drivers of purchase intent?
  • Are there are any interactions within the brand funnel purchase process?
  • What is the effect of the relationship between key brand drivers like brand consideration and purchase intent on sales?
  • What is the optimal media mix to maximize brand performance and sales objectives?


UVA Datapalooza – The Business of Data

blog-img-big-11Datapalooza is a showcase of the data-driven research, resources, services, and outreach at the University of Virginia. Presented by the DSI with co-sponsorship from the VPR and VP for IT offices, this pan-University event is an opportunity for all members of business/academic professionals to understand and appreciate the power of data to drive research and innovation, as well as decision-making, policy, and teaching methods.
In an innovation economy, companies are always looking for their next competitive edge. Data and analytics are often at the center of these discoveries, and many industries are only beginning to scratch the surface of possibilities unearthed by data science. Learn from the business leaders in our community how data and analytics are driving business decisions, while learning of specific use cases across a variety of industry domains.



blog-img-big-10Analytical insights are only valuable if you can take actions on them and more importantly in a timely fashion to improve customer engagement and loyalty. This is the place where predictive data driven marketing has a measurable impact in driving your business. However, most data driven marketing programs are developed around providing insights into what’s happened in the past, and what’s worked or not worked. However, being ‘only data driven is no longer going to be enough unless you are able to derive insights which are predictive of the future and helps organizations move forward.

At the conference, Neeraj Kulkarni shared his experiences on the steps marketing professionals need to take towards becoming a predictive data driven marketer:




By Neeraj Kulkarni

A recent Fournaise Group global marketing effectiveness study showed that 70% of CEO’s think marketers misunderstand (misuse) the business definition of terms like ROI and have lost trust in their ability to prove effectiveness of marketing spend to drive business goals. Most marketers are still challenged by their strategy and analytic teams working in silos and producing individual channel performance results for mass media (TV, Radio etc.) and online media as if each works in isolation. This approach can leady to faulty reasoning and can lead to millions of dollars being allocated in the channels which don’t yield the highest marginal ROI. The reality is that consumers today are exposed to several media touch points and sales channels. The brand funnel is no longer linear but highly connected with various channels playing a part in the decision making process. Marketers are looking to get clear understanding and solutions to the following 3 key questions:

  1. What are the key business and marketing drivers that impact sales? How do we quantify their synergistic effects to compute contribution and marginal ROI for individual channels?
  2. What is the optimized marketing allocation that will drive brand purchase intent and business objectives?
  3. What are the strategic decisions that need to be made based on the model findings to hit or exceed your brand and business goals?


Current approaches & shortcomings

Marketing mix modeling (MMM) is use of advanced analytics and statistical techniques specifically developed to estimate the impact of marketing activities on sales and then forecast the impact of future sets of activities on business goals. However too often marketing mix models are developed by utilizing only data inputs which are either media or marketing related activities and some seasonal factors. However they rarely take into knowledge inputs from key stakeholders in the organization on future outlook of business, product innovation, management changes and marketing activities. Such naïve modeling approaches are backward looking and depend on past marketing activities to be predictive of future sales or brand behavior and rarely reflect forward looking organizational beliefs and are generally not used for strategic decision making. Due to the dynamic nature of the business and market conditions, this modeling approaches fail to accurately identify and quantify the key marketing drivers which can often lead to serious misallocation of marketing resources.


Customer Intelligence + Experiential Knowledge = Actionable, Predictive Insights

At CIEK, we have developed a marketing mix solution suite which integrates big data and user experience using advanced data sciences and machine learning techniques that are transparent, predictive and highly actionable.  This forward looking approach leverages a data strategy which can take in to account data gaps, uncertainties in current business and marketing conditions and allows marketers to test new channels, messages and product mixes to accurately predict the impact of those changes on business objectives. Synergistic impact between cross channel activities are quantified to understand contribution and marginal ROI of marketing activities which can influence media and brand experience planning. Marketers can run scenarios, test marketing plans and run their campaigns with greater confidence.  Campaign analysis and learnings act as feedback to the modeling process to constantly validate and fine tune the model results. Strategic recommendations are provided based on the model findings which not only inform media allocations but more importantly provide decision support for strategic planning to drive business goals.


Marketing Leaders – Create Accountability and Drive Growth

The best way to drive organic growth in an organization is by improving current customer lifetime value and developing predictive marketing strategies for high value acquisitions. We all know that. Yet how many times have we seen marketing dollars being wasted over activities which seem to have limited impact on the core business objectives of the organization. Marketers need to drive accountability and utilize fact based decision support to drive their strategies and maximize the impact of marketing activities on their business.