The other day I Skyped with my longtime friend Miguel Maldonado who joined SAS in May 2007. In his role he helps companies and institutions make sense of the data they have access to, and how to use analytics to effectively answer their business questions.

Miguel’s passion for business analytics has also expanded into the academic field as he received his PhD in Management Sciences from Esade Business School- Ramon Lull University, Barcelona, Spain, and has been researching as an invited professor in this promising area. He is also a publisher of multiple research papers and articles.

So let’s get started with a couple of questions for Miguel.


Miguel, today it’s all about Data, Big Data as we call it now. How do we make best sense of the volume of data to make better decisions?

Hello Tom, First at all, it is a pleasure to talk to you and let me thank you for this opportunity and for your interest in these topics.

I would like to start by saying that many organizations have been certainly managing volumes of data for years. But, what is different now? Well, typically firms were focused on analyzing “internal” data sources, such as financial records, sales records, operational records, usually coming from an Enterprise Resource Planning System (ERP). And basically, this data is accessible using predefined layouts or rules, or what is called “structured” data. The advantage today is that technology facilitates to go a step ahead by integrating into the analysis other innovative data types, or “non-structured” data, such as text, voice, logs, streaming or video. Even more, traditional sources of data have similarly evolved and firms may easily take input now not only from internal systems (ERPs, CRMs, etc.), but also, from data existing in their ecosystem, or “external” data. For instance, social media is playing an important role here, letting firms gain access to incremental data existing as comments from relevant actors and third parties in these social networks.

And organizations are realizing the huge potential of transforming this raw big data (structured plus unstructured) into smart data: creating value by conducting analyzes that reveal new or uncovered patterns existing in current business transactions. All these analyzes empower the process of making better-informed decisions, transforming plain data into actions. Data is a tool for enhancing intuition!

Some practical cases where organizations are generating strong value from applying business analytics over big data include areas such as: a) Customer Experience/Personalization, b) Business Operations Optimization, c) Quality of Services and d) Delivery New Services/Products. By the way, a common ingredient for the success of these experiences is the fact that business cases and business objectives have orchestrated the underlying big data initiative.

Well, as you can see, it is not only a matter of pure volume, it is also a matter of variety, velocity and value of data! And we need analytics to materialize advantages under this new challenging context! It seems that big data and business analytics are going to be with us for a while!

We all know that Social Media and relevant data helped elect Obama as the President of the United States. It was a novum for most people 8 years ago. What has changed since this election victory and how in the current election of the new president data and social media can be even leveraged further?

You are absolutely right Tom: Public opinion got a first taste of how big data (mainly from social media) and analytics could impact a political race in 2008. Even more, several experts nominated later, in 2012, the US Presidential as the first election driven by social media, when President Obama set a new standard for promoting the use of social media and analytics in elections. Two events highlight the significant use of Twitter, for instance, in this race: the first presidential debate passed a Twitter milestone, generating 10.3 million messages from the audience for that event alone and, after his victory, President Obama sent out the most shared tweet in history at that moment, a picture of him and the First Lady, which received over 800,000 retweets with added comments.

What has changed since this election? Well, new social networks have appeared in the scene and their rates of adoption have significantly augmented. As a reference, a study conducted by the Pew Internet Project’s research concludes that, as of 2014, 74% of online adults use social networking sites. What are the opportunities in the current election? These social networks introduce today an invaluable source of data and candidates and their political staff may consolidate a significant advantage by applying analytics methods, such as text mining, to get a better understanding of who are their target constituents, what are they saying, who are the influencers, etc. This represents an inestimable input not only to organize key messages but also, to monitor the execution of the campaign based on “real-time” feedback gathered from social media.

Miguel, tell me how much can Social Media predict voter intentions in elections?

There are several studies that have demonstrated the significant correlation between findings from traditional polls and preferences expressed through social media. More ambitious analyzes have explored how content from social media could be used to propose reliable predictions in political elections. Preliminary studies have evolved from applying simple techniques focused on the volume of data related to candidates, such as counting the numbers of followers in social media as an indicator of electoral endorsement, to more sophisticated alternatives combining text mining and forecasting to infer statistical predictions by analyzing the opinions gathered from social media. Findings in this latest area have been really promising!

If yes, can we accurately predict the outcome of the presidential election ahead of time with smarter and smarter business analytics tools in hand?

Good news is that recent studies have demonstrated that it is feasible to employ analytical methods over data gathered from social media to predict the outcome of political elections. I have the opportunity to lead two of these studies: a) the case of the 2012 US Presidential Election and b) the case of the 2012 Dominican Republic Presidential Election. By applying text mining and forecasting algorithms over data gathered from Twitter, the proposed procedure consistently predicted the victor from several weeks before the Election Day, in both cases. Even more, predictions obtained from this procedure outperformed several projections announced by specialized firms in traditional political polls.

What new analytics tools will help business and consumers take advantage of Big Data?

In my opinion, an in-memory analytics platform that orchestrates data management, preparation, and exploration to model development and governance is the most powerful and sophisticated way to extract value and take advantage of Big Data. Specifically, an in-memory suite of analytic solutions that empowers analysts to develop predictive models (including those using text) and delivers insights in seconds/minutes, without the data movement that occurs in traditional BI platforms. In addition, this in-memory platform needs to be prepared to interact, easily and transparently, with the Hadoop ecosystem, the new paradigm in place to manage massive volume of both structured and unstructured data.

Finally, Miguel how in a nutshell can Big Data provide a better consumer experience in business and private?

Big data and analytics help organizations capitalize on the different views of data, capturing customer’s facts from diverse interactions, such as on-line stores, websites, social media, mobile devices, points of sales, etc. By taking advantage of these facts and integrating them, analytics may suggest innovative actions based on statistical predictions, such as what item would be the “next best product to offer” to every customer. Big data analytics empower organizations, and particularly marketers, to move from the generic “one-size-fits-all” tactics to a real personalized value, where they can finally propose actions specific to us as individuals, invigorating the real customer experience.

Now a couple of personal questions to Miguel.

How do you spend your free time when not analyzing data?

I really enjoy engaging in outdoor activities, especially sailing and biking with friends. Great learning opportunities abound in nature…and I always learn something new every single time I engage in these activities!

Either Or?

  1. Tapas                     or         5 Course Dinner


  1. Real Madrid             or         Bayern Munich

Barcelona FC! 😉

  1. Twitter                     or         Facebook

ummm…. I’d say Twitter!

  1. San Francisco         or       Palo Alto

It depends on the purpose of the visit!

  1. Malbec                     or        Brandy

Malbec. May I suggest the Catena Zapata Malbec Nicasia Vineyard La Consulta 2011? 😉

  1. Soccer                     or         Swimming

Water polo!

  1. Mountains               or       Beaches


  1. Steak / Frites          or       Salad