In my last post, I noted that the flexibility provided by the concept of the schema-on-read paradigm that is typical of a data lake had to be tempered with the use of a metadata repository so that anyone wanting to use that data could figure out what was really in
As mass marketing becomes less common and effective, we get closer and closer to the ideal of the “segmentation of one,” which involves high degrees of personalization. In that environment, businesses must be able to market to customers at an individual level to remain competitive and relevant. However, without customer analytics technologies --
As a linguist, I am fascinated with words, their meanings and use. So when I recently saw the words “learning analytics” in a conference paper title, I started thinking about the prevalence of the word “analytics” itself. In the last decade, we have preceded “analytics” with many modifiers referring to
The term “disruptive technologies” frightens many organizations, but to companies like Alibaba, Uber, Airbnb and Facebook, it’s the secret to their success. These four companies from unrelated industries have one major commonality: They don’t “own” anything, at least not in the traditional sense. What they provide is a digital service,
In my first blog post in the Education meets Big Data blog series, I explained the need for Statewide Longitudinal Data Systems(SLDS). In the blog post following, I shared an interview with Armistead Sapp, one of the authors of the book, "Implement, Improve and Expand Your Statewide Longitudinal Data System." In this
I've spent a great deal of time in my consulting career railing against multiple systems of record, data silos and disparate versions of the truth. In the mid-1990s, I realized that Excel could only do so much. To quickly identify and ultimately ameliorate thorny data issues, I had to up
SAS is hosting this year’s European Analytics 2015 conference in Rome November 9 – 11. This three-day inspiring event will give you the chance to boost your company’s analytics culture in an international environment to make sure your knowledge and expertise meet the demands of the digital era. But what if
Now that another summer of 12-hour family road-trips to Maine and Ohio, pricey engineering and basketball camps for the kids, and beating the heat at the beach are over, I've taken a fresh look at what people are focused on with their data – and what SAS is providing in the data management space.
In response to my last post—Marketers ask: Why do we need Hadoop if we’re not doing big data?—a Twitter follower asked this question: It’s a fair question. Typically, marketers are more interested in the car (in this case, big data) than they are in the engine (Hadoop). But Hadoop is
¿Alguna vez ha pensado cuántas decisiones importantes debe tomar en la vida? Por suerte no son tantas: a qué colegio o universidad ir, casarse o no casarse, tomar un trabajo o no, en dónde vivir… etc. Nunca habrá una “penúltima” respuesta para estas decisiones, pero todas ellas necesitan de nuestros
A few of our clients are exploring the use of a data lake as both a landing pad and a repository for collection of enterprise data sets. However, after probing a little bit about what they expected to do with this data lake, I found that the simple use of
While discussing ways and means to improve Sales and Operations Planning (S&OP) and forecasting, many a time business executives ask “What can we do with social media?" This was definitely NOT a usual topic in S&OP forum just a few years back! Most of the time, I push back the
It’s been very hot here in Northern Italy: electricity provision has struggled to keep up and we’ve had frequent power outages in the area, even within our apartment building. A bit inconvenient? Don’t get me started. I feel like my home appliances have turned against me, taking me back to
La ciencia de datos se ha convertido en un concepto muy usado últimamente. No tiene una definición clara ya que varias organizaciones y personas lo han clasificado de diferentes maneras, incluso algunas lo han etiquetado simplemente como una ciencia más, pero esto no es así. Los que ya practican esta
In my previous post I talked to John Cassara about the growing threat of mobile payments and how mobile phones can be used to launder illicit funds globally. I spoke with him again recently on the topic of financial intelligence. Here are the highlights from our discussion. So what is
.@philsimon offers his definition of the term.
Bigger doesn’t always mean better. And that’s often the case with big data. Your data quality (DQ) problem – no denial, please – often only magnifies when you get bigger data sets. Having more unstructured data adds another level of complexity. The need for data quality on Hadoop is shown by user
“Un científico de datos es una persona que es mejor estadístico que un ingeniero de sistemas y que es mejor ingeniero de sistemas que cualquier estadístico”, Jorge Quiroga, CEO de Blacksip. Ese es el tono en el que se habla hoy de los científicos de datos. Tono que si le
In the oil and gas industry, analytics are used to improve both upstream and downstream operations, from optimizing exploration and forecasting production to reducing commodity trading risk and understanding customer's energy needs. If you plan to derive value from the digital oil field, big data, and analytics, one of the first things
Oh, how times have changed during my 20-plus years in the insurance industry. Data wasn’t a word we used much back in the 80s and 90s, unless of course you worked in those arcane and mysterious IT data centres. Even amidst the computerisation of the insurance industry in the 80s, many
Oh, how times have changed during my 20-plus years in the insurance industry. Data wasn’t a word we used much back in the 80s and 90s, unless of course you worked in those arcane and mysterious IT data centres. Even amidst the computerisation of the insurance industry in the 80s, many
In my previous blog post, I discussed the benefits of a Statewide Longitudinal Data System (SLDS) and shared a SAS book on the subject: Implement, Improve and Expand Your Statewide Longitudinal Data System by Armistead W Sapp III and Jamie McQuiggan. Today, I'm sharing a conversation I had with one of the book’s authors,
In the movie Minority Report, while the leading actor walks through the mall and experiences personalized greetings all around him, there is a clear flash of how the future of marketing may look: a customer journey marked by relevant and personalized experiences. Getting back to the reality of today, the typical
You have to be "in it to win it" as they say. This is becoming the case for many organisations that need to start using data to make better, evidence-based business decisions. Today, using analytics is not so much a data lottery as a data necessity. Some businesses may not
During a lighthearted moment in a serious conversation, Howard Schmidt, cyber security advisor to multiple presidents, told a Wall Street Journal interviewer that relying on a government agency as your primary backstop during a major cyber security breach is akin to calling Ghostbusters: you might not get the help you
"Our corporate data is growing at a rate of 27% each year and we expect that to increase. It’s just getting too expensive to extend and maintain our data warehouse.” “Don’t talk to us about our ‘big’ data. We’re having enough trouble getting our ‘small’ data processed and analyzed in
The amount of data being produced and captured from the plant floor today is staggering. When you add it all up, a factory can easily generate over 34 Terabytes of data per day, or nearly 9 Petabytes a year - that's 9 Million Gigabytes! Yet, with all of those systems, and all
We’ve been talking about data recently at the Analytic Hospitality Executive. I’ve advocated to use whatever data you have, big or small, to get started today on analytic initiatives that will help you avoid big data paralysis. In this blog, I’m going to get a bit more technical than usual
Durante los últimos años, Tamara Dull, directora de tecnologías emergentes para SAS Best Practices, ha escrito mucho sobre Big Data. Sus conclusiones son interesantes: pensamos que el big data es algo nuevo, pero la verdad, hemos lidiado con él durante años; el correo electrónico, las fotos, los videos, los archivos
What's that productivity related quote by Charles Dickens? "My advice is never do tomorrow what you can do today." For years, machine learning has been written about and discussed widely with a focus on the benefits it will bring in the near future. But guess what? The future for machine learning
