Data Science

Getting Started with Cloudera Data Science Workbench

Last week, Cloudera announced the General Availability release of Cloudera Data Science Workbench. In this post, I’ll give a brief overview of its capabilities and architecture, along with a quick-start guide to connecting Cloudera Data Science Workbench to your existing CDH cluster in three simple steps. At its core, Cloudera Data Science Workbench enables self-service data science for the enterprise. Data scientists can build, scale, and deploy data science and machine learning solutions in a ...Read More

12 Best Practices for Big Data and Data Science

The 12 best practices for big data and data science along with a few comments about why each is important. Think of the best practices as recommendations that can guide your organization into successful implementations of big data and data science. Get your data in order. The right data management strategy is important to big data and data science success. In the zeal to get started analyzing data, organizations often don’t pay attention to that data. Yes, it is OK to experiment on raw data; a g...Read More

The State of Big Data and Data Science

Although there has been a lot of market hype and excitement around big data and data science, this does not necessarily mean that it has widely penetrated in most organizations. As previously mentioned, a little more than a third of our respondents believe they have a big data and analytics program in place now, and another third plan to have one within the year. We asked respondents where they are now in terms of assembling large volumes of data and using different data types for analytics, as ...Read More

The hard to find Data Scientist

One of the biggest things that can put a damper on big data analytics programs has nothing to do with deploying and managing advanced analytics tools—it’s the challenge of hiring and retaining skilled data scientists who can put the tools you’ve installed to good use. In a survey of business intelligence, analytics and data management professionals conducted by TDWI in the second half of 2015, a lack of skilled personnel ranked second on a list of top challenges that organizations face in trying...Read More

Building the LinkedIn Data Science Team

Reference: Building Data Science Teams ,The Skills, Tools, and Perspectives Behind Great Data Science Groups – DJ Patil I’m proud of what we’ve accomplished in building the LinkedIn data team. However, when we started, it didn’t look anything like the organization that is there today. We started with 1.5 engineers (who would later go on to invent Voldemort, Kafka, and the real-time recommendation engine systems), no data services team (there wasn’t even a data warehouse), and five analysts...Read More

13 Data Scientist You Must Follow on Twitter: International Women’s Day Edition

Women are 50% of the world population, and only hold 23% of STEM roles worldwide. The rise of data science is offering women a clearer path to success in technology. It is happening right now. For #IWD2017 here’s a list of 13 inspiring women who work in data science and are changing technology forever. 1. Renee M. P. Teate, documenting her path from “SQL Data Analyst pursuing an Engineering Master’s Degree” to “Data Scientist” Woo! Thanks for supporting!! (Eve...Read More

The Roles of a Data Scientist

In every organization I’ve worked with or advised, I’ve always found that data scientists have an influence out of proportion to their numbers. The many roles that data scientists can play fall into the following domains. Decision sciences and business intelligence Data has long played a role in advising and assisting operational and strategic thinking. One critical aspect of decision-making support is defining, monitoring, and reporting on key metrics. While that may sound easy, there is a real...Read More

Insights-Driven practices using Data Science Tools

In September 2016, DataScience commissioned Forrester Consulting to examine the differences between high-growth firms using insights-driven practices such as data science, and everybody else. Specifically, they wanted to find out if a platform that unifies the entire life cycle of data science work could accelerate a firm’s competitive advantage through insights. Forrester conducted 10 in-depth interviews and an online survey of 208 decision-makers in business/customer insights, data science, an...Read More

Easy-to-use data science tools power new startup

At DonorBureau, a startup in the nonprofit space, easy-to-use tools for data science are a must. Lucky for the company, that’s where the analytics software industry is going. More data science tools are available today than ever before, and that’s good news for companies occupying smaller niches. It means they have access to tools that fit their needs, whether large or small. “We’re dealing with a very unique niche of organizations, so it’s different than if youR...Read More

Women in Data Science, Strength and Empowerment

On Friday February 3rd, took place the Women in Data Science Conference (#WiDS2017), which happened at 80+ locations worldwide with live stream from Stanford University. It was an amazing event, where you were able to learn how many professional women are making sense out of data, their latest data science related researches in multiple domains and how they are using data science for success at their companies. I was invited to the WIDS2017 conference at the Miami location by the WIDS Florida Am...Read More

Data Scientist Interview Series: Q&A with Davi Abdallah

We are running a series of interviews with several Data Scientist working for top companies, their vocation, how they started and what is their message for the future professionals in this increasing market demanding career. Davi Abdallah is the Data Scientist at JetSmarter, the fastest growing private jet company in the world. Davi started his career as a Systems Analyst, and worked his way up into the BI/Data field. He worked for top companies like Wells Fargo, Microsoft and AutoNation. Here a...Read More

Should I Run with a Pace Group

Probably, at least according to data from the Dublin City Marathon. TLDR; Should I run with a pace group? Based on the data from the Dublin City Marathon, if there is a pace group that matches your target time then it is likely to help your performance on the day. Pace groups do have an impact on a race: there are large spikes in the number of runners finishing at paced finish-times compared to unpaced finish-times. Changing the paced times, changes the finisher spikes. Running with a pace group...Read More

Building The LinkedIn Knowledge Graph

At LinkedIn, we use machine learning technology widely to optimize our products: for instance, ranking search results, advertisements, and updates in the news feed, or recommending people, jobs, articles, and learning opportunities to members. An important component of this technology stack is a knowledge graph that provides input signals to machine learning models and data insight pipelines to power LinkedIn products. This post gives an overview of how we build this knowledge graph. LinkedIn’s ...Read More

The Simpsons by the Data

Analysis of 27 seasons of Simpsons data reveals the show’s most significant side characters, a pattern of patriarchy, declining TV ratings, and more The Simpsons needs no introduction. At 27 seasons and counting, it’s the longest-running scripted series in the history of American primetime television. The show’s longevity, and the fact that it’s animated, provides a vast and relatively unchanging universe of characters to study. It’s easier for an animated show to scale to hundreds of recurring ...Read More

Battle of the Data Science Venn Diagrams

Data science is a rather fuzzily defined field; some of the definitions I’ve heard are: “Work that takes more programming skills than most statisticians have, and more statistics skills than a programmer has.” “Applied statistics, but in San Francisco.” “The field of people who decide to print ‘Data Scientist’ on their business cards and get a salary bump.” Personally, I’ve recently decided to avoid the controversy by calling myself a d...Read More

Learn the Art of Data Science in Five Steps

The field of data science is one of the youngest and most exciting fields in the technology sector. In no other industry or field can you combine statistics, data analysis, research, and marketing to do jobs that help businesses make the digital transformation and come to full digital maturity. In today’s business world, companies can no longer afford to look at their websites and social media presences as add-ons or after thoughts. The success of the technological aspects of a company is as cru...Read More

The Art of Data Science: The Skills You Need and How to Get Them

The meteoric growth of available data has precipitated the need for data scientists to leverage that surplus of information. This spotlight has caused many industrious people to wonder “can I be a data scientist, and what are the skills I would need?”. The answer to the first question is yes – regardless of your prior experience and education, this role is accessible to motivated individuals looking to meet this challenge. As for the second question, the necessary skills (some formal and some mo...Read More