- KDnuggets™ News 21:n16, Apr 28: Data Science Books You Should Start Reading in 2021; Top 10 Must-Know Machine Learning Algorithms for Data Scientists - Apr 28, 2021.
Data science is not about data – applying Dijkstra principle to data science; Data Science Books You Should Start Reading in 2021; How to ace A/B Testing Data Science Interviews; Top 10 Must-Know Machine Learning Algorithms for Data Scientists – Part 1; Production-Ready Machine Learning NLP API with FastAPI and spaCy
- What did COVID do to all our models? - Apr 2, 2021.
An interview with Dean Abbott and John Elder about change management, complexity, interpretability, and the risk of AI taking over humanity.
- Kedro-Airflow: Orchestrating Kedro Pipelines with Airflow - Mar 12, 2021.
The Kedro team and Astronomer have released Kedro-Airflow 0.4.0 to help you develop modular, maintainable & reproducible code with orchestration superpowers!
- How I Got 4 Data Science Offers and Doubled my Income 2 Months After Being Laid Off - Jan 19, 2021.
In this blog, I shared my story on getting 4 data science job offers including Airbnb, Lyft and Twitter after being laid off. Any data scientist who was laid off due to the pandemic or who is actively looking for a data science position can find something here to which they can relate.
- Mastering Time Series Analysis with Help From the Experts - Oct 28, 2020.
Read this discussion with the “Time Series” Team at KNIME, answering such classic questions as "how much past is enough past?" others that any practitioner of time series analysis will find useful.
- The Ethics of AI - Oct 21, 2020.
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about a very important subject - the ethics of AI.
- How to ace the data science coding challenge - Oct 15, 2020.
Preparing to interview for a Data Scientist position takes preparation and practice, and then it could all boil down to a final review of your skills. Based on personal experience, these tips on how to approach such a review will help you excel in the coding challenge project for your next interview.
- Recommender Systems in a Nutshell - Jul 23, 2020.
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about recommender systems and the ways they are used.
- How to Think Like a Data Scientist - May 29, 2020.
So what does it take to become a data scientist? For some pointers on the skills for success, I interviewed Ben Chu, who is a Senior Data Scientist at Refinitiv Labs.
- Chatbots in a Nutshell - May 7, 2020.
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about chatbots and the ways they are used.
- How to land a Data Scientist job at your dream company - Jan 31, 2020.
Job hunting for anyone just starting out as a data scientist can require grit, passion, and perseverance before finding the best opportunity. Follow this career search journey to learn what it took -- and the learning resources used -- to land the dream job.
- KDnuggets™ News 20:n04, Jan 29: AutoML: If you try it, you’ll like it more; The Data Science Interview Study Guide - Jan 29, 2020.
AutoML Poll results: if you try it, you'll like it more; The Data Science Interview Study Guide; What Do Data Scientists in Europe Do & How Much Are They Worth?; 2 Questions for a Junior Data Scientist
- 2 Questions for a Junior Data Scientist - Jan 24, 2020.
Academic credentials and experience with previous machine learning projects are important for kicking off a data science career. However, landing your first job out of school will require you to extend your thinking about projects and problems. Learn how one interviewer honed in on desired skills by considering these two questions.
- KDnuggets™ News 19:n39, Oct 16: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI - Oct 16, 2019.
This week on KDnuggets: Beyond Word Embedding: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI; Activation maps for deep learning models in a few lines of code; There is No Such Thing as a Free Lunch; 8 Paths to Getting a Machine Learning Job Interview; and much, much more.
- Automated Machine Learning: Just How Much? - Sep 5, 2019.
This is an interview between Rosaria Silipo and data scientists Paolo Tamagnini, Simon Schmid and Christian Dietz, asking a few questions on the topic of automated machine learning from their point of view, and some interesting examples of its practical use.
- Secrets to a Successful Data Science Interview - Jul 15, 2019.
Are you puzzled as to what to prepare for data science interviews? That you are reading this document is a reflection of your seriousness in being a successful data scientist.
- Spatio-Temporal Statistics: A Primer - Apr 5, 2019.
Marketing scientist Kevin Gray asks University of Missouri Professor Chris Wikle about Spatio-Temporal Statistics and how it can be used in science and business.
- Data Science for Decision Makers: A Discussion with Dr Stelios Kampakis - Mar 26, 2019.
This article contains an interview veteran data scientist, Dr Stylianos (Stelios) Kampakis, in which he discusses his career, and how he helps decision makers across a range of businesses understand how data science can benefit them.
- Natural Language Processing for Social Media - Feb 12, 2019.
Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about Natural Language Processing and how it is used in social media analytics.
- How to Adopt Machine Learning: Interviews with Technical & Business Leaders - Feb 11, 2019.
This 8 chapter series includes interviews with technical and business leaders from a number of large companies with the aim to help you adopt machine learning in your organization.
- Cracking the Data Scientist Interview - Jan 29, 2019.
After interviewing with over 50 companies for Data Scientist/Machine Learning Engineer, I am going to frame my experiences in the Q&A format and try to debunk any myths that beginners may have in their quest for becoming a Data Scientist.
- Skip the Interview! 9 Benefits of Career Fairs - Aug 29, 2018.
Career fairs are a great way to get your feet wet if you’re just starting your data science career, or to be exposed to newer trends and emerging organizations if you’re already established. What other ways are career fairs beneficial?
- KDnuggets™ News 18:n30, Aug 8: Iconic Data Visualisation; Data Scientist Interviews Demystified; Simple Statistics in Python - Aug 8, 2018.
Also: Selecting the Best Machine Learning Algorithm for Your Regression Problem; From Data to Viz: how to select the the right chart for your data; Only Numpy: Implementing GANs and Adam Optimizer using Numpy; Programming Best Practices for Data Science
- Netflix Data Science Interview Questions: Acing the AI Interview - Jun 7, 2018.
Gain some perspective on the Netflix interview process, and on ways to prepare for just such an industry interview.
- Deep Conversations: Lisha Li, Principal at Amplify Partners - May 3, 2018.
Mathematician Lisha Li expounds on how she thrives as a Venture Capitalist at Amplify Partners to identify, invest and nurture the right startups in Machine Learning and Distributed Systems.
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- Data Science Interview Guide - Apr 25, 2018.
Traditionally, Data Science would focus on mathematics, computer science and domain expertise. While I will briefly cover some computer science fundamentals, the bulk of this blog will mostly cover the mathematical basics one might either need to brush up on (or even take an entire course).
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- The Two Sides of Getting a Job as a Data Scientist - Mar 7, 2018.
Are you a Data Scientist looking for a Job? Are you a Recruiter looking for a Data Scientist? If you answered yes or NO to this questions you need to read this.
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- KDnuggets™ News 18:n10, Mar 7: Functional Programming in Python; Surviving Your Data Science Interview; Easy Image Recognition with Google Tensorflow - Mar 7, 2018.
- How to Survive Your Data Science Interview - Mar 1, 2018.
There are many wonderful things about data science. It’s extreme breadth is not one of them. The title of data scientist means something different at every company
- A Guide to Hiring Data Scientists - Feb 22, 2018.
This article provides a short overview of emerging data scientist types and their unique skillsets, as well as a guide for HR professionals and analytics managers who are looking to hire their first data scientists or build a data science team. Included are an overview of skills for each type and specific questions that can be asked to assess candidates.
- Learn Data Science Without a Degree - Jan 19, 2018.
But how do you learn data science? Let’s take a look at some of the steps you can take to begin your journey into data science without needing a degree, including Springboard’s Data Science Career Track.
- An Inside Update on Natural Language Processing - Jun 28, 2016.
This article is an interview with computational linguist Jason Baldridge. It's a good read for data scientists, researchers, software developers, and professionals working in media, consumer insights, and market intelligence. It's for anyone who's interested in, or needs to know about, natural language processing (NLP).
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- SAP Predictive Analytics Interview with Sven Bauszus - May 26, 2016.
I talk with Sven Bauszus, SAP Predictive Analytics global leader, about their main products in Business and Predictive Analytics and Big Data space, analytics maturity by industry, the automation of Data Science, and "citizen" Data Scientists.
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- 5 Ways Data Scientists Keep Learning After College - Dec 17, 2015.
Taken from the answers experts gave, here is a compiled list of 5 essential actions and attitudes that keep data scientists learning after their degrees.
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- Crushed it! Landing a data science job - Oct 1, 2015.
Data scientist interviews depend on the company and the team, it might look like a software developer’s interview, or statistician’s interview. Here we collected some hot tips to pass along if you’re thinking about a move soon.
- Interview: Stefan Groschupf, Datameer on Why Domain Expertise is More Important than Algorithms - Aug 6, 2015.
We discuss large-scale data architectures in 2020, career path, open source involvement, advice, and more.
- Interview: Stefan Groschupf, Datameer on Why SQL on Hadoop is a Bad Idea - Aug 5, 2015.
We discuss the startups landscape in Big Data, valuation of Big Data companies, recognition earned by Datameer, and why SQL on Hadoop is a bad idea.
- Interview: Stefan Groschupf, Datameer on Balancing Accuracy and Simplicity in Analytics - Aug 4, 2015.
We discuss common pain points in Big Data projects, evolution of Datameer technology, department specific solution – Datameer Professional, Datameer 5.0 Smart Execution, tacking over-simplicity and more.
- Interview: Andrew Duguay, Prevedere on the Hidden Value in Global Data Sets - Jul 31, 2015.
We discuss the challenges in analyzing global economic datasets, impact of Big Data growth on economics, desired skills in data scientists, and more.
- Interview: Andrew Duguay, Prevedere on Economic Intelligence from Integrating Public Datasets - Jul 30, 2015.
We discuss Analytics at Prevedere Software, understanding the impact of external factors on a company’s performance, features of in-memory correlation engine and economic intelligence by Prevedere.
- Interview: Brian Kursar, Toyota on Big Data & Advanced Analytics – Cornerstones of Innovation - Jul 28, 2015.
We discuss the Big Data architecture at Toyota, executives’ perception of Analytics, Toyota Innovation Fair, advice, trends, and more.
- Interview: Thanigai Vellore, Art.com on Why Big Data vs RDBMS is the Wrong Question - Jul 24, 2015.
We discuss success factors with polyglot architectures, Big Data challenges, recommendations for using Big Data technologies, trends, advice, and more.
- Interview: Thanigai Vellore, Art.com on Delivering Contextually Relevant Search Experience - Jul 23, 2015.
We discuss the role of Analytics at Art.com, the polyglot data architecture at Art.com, the use cases for Hadoop, vendor selection, supporting semantic search and experience with Avro.
- Interview: Ali Vanderveld, Groupon on How Data Science is Changing the Global E-commerce Marketplace - Jul 17, 2015.
We discuss the tools used for data science, competitive landscape, journey from astrophysics to data science, advice, skills sought in data scientists, and more.
- Interview: Ali Vanderveld, Groupon on Vital Ingredients of Analytics-powered Sales Force - Jul 16, 2015.
We discuss the role of Analytics at Groupon, deciding factors for merchant priority, limitations of historical data, optimizing the efforts of sales force, data characteristics and dealing with Data Sparsity.
- Interview: Ramkumar Ravichandran, Visa on Customer-focus Mindset for Analytics - Jul 15, 2015.
We discuss career advice, need for customer-focus, Analytics trends, desired skills in Data Science practitioners, and more.
- Interview: Ramkumar Ravichandran, Visa on Actionable Insights – Easier Said Than Done - Jul 14, 2015.
We discuss Analytics at Visa, adapting to the Big Data world, gaps between expectations and delivery from Analytics, delivering Actionable Insights, and tools/technologies used.
- Interview: Reiner Kappenberger, HP Security Voltage on Security Checklist for Data Architectures - Jul 10, 2015.
We discuss securing data-at-rest and data-in-motion, security recommendations for data architectures, trends, advice, and more.
- Interview: Reiner Kappenberger, HP Security Voltage on How to Secure Data-in-Motion - Jul 9, 2015.
We discuss the security concerns in Big Data, challenges in securing Big Data locally and over cloud, and open source solutions – Knox and Ranger.
- Interview: Reiner Kappenberger, HP Security Voltage on Data-Centric Security for Big Data - Jul 8, 2015.
We discuss HP Security Voltage growth story, HP acquisition, assessing the state of current security standards, and the need for “data-centric” security.
- KDnuggets Interview: Amr Awadallah, CTO & Co-founder, Cloudera on the Secret Sauce of Open Source - Jul 2, 2015.
We discuss the critical success factor for open source projects, entrepreneurial lessons, advice, desired qualities in data scientists and more.
- KDnuggets Interview: Amr Awadallah, CTO & Co-founder, Cloudera on the Need for Self-Service Analytics - Jun 30, 2015.
We discuss the importance of enabling self-service analytics, partnership with Cask, Big Data vendor selection and competitive landscape.
- KDnuggets Interview: Amr Awadallah, CTO & Co-founder, Cloudera on the Future of Information Architecture Design - Jun 29, 2015.
We discuss Cloudera’s achievements, story behind the name ‘Cloudera’, CTO role, and key attributes of information architecture designed for future.
- Interview: Anil Gadre, MapR on 3 Keys for Big Data Success: Reliability, Security, & Scalability - Jun 24, 2015.
We discuss the origin of Apache Myriad, state of security in Big Data, MapR Quick Start Solutions, Hadoop vendor selection criteria, and more.
- Interview: Anil Gadre, MapR on What it takes to Automate Data-to-Action? - Jun 23, 2015.
We discuss how analytics can impact the business “as-it-happens”, merging business analytics with production operations, transition challenges, and recently announced partnership with Teradata.
- Interview: Joseph Babcock, Netflix on Curiosity and Courage – Key for Success in Data Science - Jun 17, 2015.
We discuss discovery vs. personalization, advice, trends, desired skills in data scientists, and more.
- Interview: Joseph Babcock, Netflix on Genie, Lipstick, and Other In-house Developed Tools - Jun 16, 2015.
We discuss role of analytics in content acquisition, data architecture at Netflix, organizational structure, and open-source tools from Netflix.
- Interview: Joseph Babcock, Netflix on Discovery and Personalization from Big Data - Jun 15, 2015.
We discuss the steps involved in Discovery process at Netflix, impact due to multitude of devices, system generated logs, and surprising insights.
- Interview: Ranjan Sinha, eBay on Winner Insights from International Sorting Competitions - Jun 10, 2015.
We discuss advancements in the field of Personalization, lessons from winning sorting competitions, Data Science trends, career advice, and more.
- Interview: Ranjan Sinha, eBay on Advanced Hadoop Cluster Management through Predictive Modeling - Jun 9, 2015.
We discuss categorization of e-commerce analytics, opportunities/ challenges of Big Data, Astro predictive model for Hadoop cluster management, and Apache Kylin.
- Interview: James Taylor, Salesforce on Phoenix + HBase – The Future of Big Data - Jun 6, 2015.
We discuss the advantages of Phoenix, upcoming features, soon coming-up support for transactions, trends, advice, and more.
- Interview: James Taylor, Salesforce on Apache Phoenix – RDBMS for Big Data - Jun 5, 2015.
We discuss the beginning of Phoenix project, decision of making it open source, relational database layer on HBase, and key reasons for the superior performance of Apache Phoenix.
- Interview: Sheridan Hitchens, Auction.com on Data Science Evolution from a Nerdy Hobby to a Strategic Priority - Jun 4, 2015.
We discuss the evolution of Data Science expectations, Data Science as a career, advice, and more.
- Interview: Linda Powell, Consumer Financial Protection Bureau (CFPB) on Data Governance for Finance Industry - May 22, 2015.
We discuss the chief data officer role at CFPB, big data opportunities and challenges, ontology, vintage data, data governance trends, advice, and more.
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- Interview: Antonio Magnaghi, TicketMaster on Why Honesty is Key for Analytics Success - May 19, 2015.
We discuss lessons from implementing lambda architecture, impact of Big Data on recommender systems, trends, advice, and more.
- Interview: Sheridan Hitchens, Auction.com on Customer Lifetime Value as the Cornerstone for Marketing Analytics - May 15, 2015.
We discuss Customer Lifetime Value (CLV) metric, maturity level for the CLV metric, different models for calculating it, challenges in designing strategy based on CLV and tackling attribution.
- Interview: Hobson Lane, SHARP Labs on How Analytics can Show You “All the Light You Cannot See” - May 14, 2015.
We discuss the impact of rapid growth in magnitude of data, programming skills for data science, major trends, advice, data science skills, and more.
- Interview: Hobson Lane, SHARP Labs on the Beauty of Simplicity in Analytics - May 13, 2015.
We discuss Predictive Analytics projects at Sharp Labs of America, common myths, value of simplicity, tools and technologies, and notorious data quality issues.
- Interview: Mark Weiner, Temple University Health System on Addressing Healthcare Data Gaps through Advanced Simulation - May 12, 2015.
We discuss dealing with current gaps in healthcare data, challenges in using real world healthcare data, desired skills for data scientists in healthcare industry, advice, and more.
- Interview: Mark Weiner, Temple University Health System on Maturity Assessment of Healthcare Analytics - May 11, 2015.
We discuss the challenges and opportunities created by increased collection of healthcare data, state of data accessibility, and the value of Analytics to the drug development process.
- Interview: Alison Burnham, Scorebig on Optimal, Real-time Pricing through Analytics - May 8, 2015.
We discuss Analytics at ScoreBig, company’s business model, unexpected insights, challenges in customer value management, advice, and more.
- Interview: Haile Owusu, Mashable on Surviving Imprecision in Digital Media Analytics - May 1, 2015.
We discuss the challenges in tracking social media sharing, advice, important trends, and more.
- Interview: Haile Owusu, Mashable on Riding the Wave of Viral Content - Apr 29, 2015.
We discuss Mashable’s milestones, data-driven digital publishing, digital media tracking, viral prediction, and Mashable Velocity.
- Interview: Mario Vinasco, Facebook on Advancing Marketing Analytics through Rigorous Experimentation - Apr 27, 2015.
We discuss marketing analytics at Facebook, multi-channel performance assessment, success factors, lessons from Look Back feature, advice, and more.
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- Interview: Emmanuel Letouzé, Data-Pop Alliance on Big Data for Development and Future Prospects - Apr 25, 2015.
We discuss the field of Big Data for Development, current projects and future plans for Data-Pop Alliance, public participation opportunities, advice, and more.
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- Interview: Emmanuel Letouzé, Data-Pop Alliance on Democratizing the Benefits of Big Data - Apr 24, 2015.
We discuss the 3 Cs of Big Data, state of ethics in the field of Big Data, and how to ensure that the benefits of Big Data reach the masses.
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- Interview: Emmanuel Letouzé, Data-Pop Alliance on Big Data and Human Rights – A Complex Affair - Apr 22, 2015.
We discuss the founding story of Data-Pop Alliance, the applications and implications of Big Data on Human Rights and the need for penetration of Data Literacy.
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- Interview: Michael Li, Data Incubator on Bridging the Data Science Skills Gap between Academia and Industry - Apr 21, 2015.
We discuss the response from hiring companies, recommendations for aspirants, retaining data science talent, advice, and more.
- Interview: Michael Li, Data Incubator on Data-driven Hiring for Data Scientists - Apr 20, 2015.
We discuss the launch of the Data Incubator, its business model, why we need data-driven hiring, selection process for the incubator program and alumni feedback.
- Interview: Ksenija Draskovic, Verizon on Conquering Fear and Cherishing Creativity for Success in Data Science - Apr 17, 2015.
We discuss career advice, motivation, key qualities sought in Data Science practitioners, and more.
- Interview: Ksenija Draskovic, Verizon on How to Not Get Lost in the Big Data Wilderness - Apr 16, 2015.
We discuss recommendations for data-driven decision making, challenges and benefits of using unstructured data, managing expectations and key trends.
- Interview: Ksenija Draskovic, Verizon on Dissecting the Anatomy of Predictive Analytics Projects - Apr 15, 2015.
We discuss Predictive Analytics use cases at Verizon Wireless, advantages of a unified data view, model selection and common causes of failure.
- Interview: Michael Lurye, Time Warner Cable on Key Lessons from Shifting to Hadoop - Apr 14, 2015.
We discuss the key lessons from shifting to Hadoop, data management in today’s world, future of Data Science, advice and more.
- Interview: Michael Lurye, Time Warner Cable on Big Data and the Insatiable Demand for BI - Apr 13, 2015.
We discuss EDM at Time Warner Cable, data sources, complementing legacy data warehouses with Big Data solutions, vendor selection and build vs. buy decision.
- Interview: Xia Wang, AstraZeneca on Big Data and the Promise of Effective Healthcare - Apr 10, 2015.
We discuss challenges in analyzing text data, Big Data impact on translational bioinformatics, advice, desired skills in data scientists, and more.
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- Interview: Ravi Iyer, Ranker on Dealing with Inherent Bias in Crowdsourcing Data - Apr 8, 2015.
We discuss the challenges of analyzing crowdsourcing data, tools and technologies, competitive landscape, advice, trends, and more.
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- Interview: Ravi Iyer, Ranker on Why Crowdsourcing Needs Data Science - Apr 7, 2015.
We discuss the dynamics of Ranker crowdsourcing platform, key factors for effectiveness, role of data science in crowdsourcing, and more.
- Interview: Beth Diaz, Washington Post on How Dark Social is Shadowing Modern Analytics - Apr 6, 2015.
We discuss recent events at Washington Post, growth initiatives, the growing pain of Dark Social, how to deal with it, audience analytics, advice and more.
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- Interview: Alessandro Gagliardi, Glassdoor on the Indispensable Skills for Data Scientists - Apr 1, 2015.
We discuss Analytics at Glassdoor, important lessons, major factors affecting job satisfaction, challenges of working on Twitter Data, indispensable components of Data Science education.
- Interview: Satyam Priyadarshy, Halliburton on Unlocking Success for Big Data Projects - Mar 31, 2015.
We discuss Predictive Analytics in Oil & Gas industry, Big Data analytics, key drivers of success,common reasons of failure, trends, advice, and more.
- Interview: Satyam Priyadarshy, Halliburton on Big Data Challenges in Oil & Gas Industry - Mar 30, 2015.
We discuss Analytics at Halliburton, Big Data challenges unique to Oil & Gas industry, and the 7 V’s of Big Data.
- Interview: Beena Ammanath, GE on Data Science – It’s Not Just Science! - Mar 24, 2015.
We discuss benefits and challenges of Data Lake, trends, life lessons, motivation, desired skills, and more.
- Interview: Beena Ammanath, GE on the Industrial Internet for Data-driven Innovation - Mar 23, 2015.
We discuss the role of Analytics at GE, Industrial Internet and how it is different from consumer internet, and the key capabilities of Predix.
- Interview: Brad Klingenberg, StitchFix on Decoding Fashion through Analytics and ML - Mar 21, 2015.
We discuss the challenges in making personal styling recommendations, unexpected insights, interesting trends, motivation, advice, desired qualities in data scientists and more.
- Interview: Vince Darley, King.com on What do you need to become Top Grossing Game - Mar 19, 2015.
We discuss common characteristics of games that achieved top ranking, career advice, trends, desired qualities in data scientists and more.
- Interview: Dave McCrory, Basho on Why Data Gravity Cannot be Ignored in Architecture Design - Mar 17, 2015.
We discuss data gravity and its implications, Riak Enterprise 2.0, Riak CS 1.5, competitive landscape, challenges and more.
- Interview: Dave McCrory, Basho on Distributed Database Needs of a Future Enterprise - Mar 16, 2015.
We discuss the future of distributed storage for enterprise, Scale-up vs. Scale-out, software design patterns in Cloud era, microservices model and the place for legacy database in modern enterprise IT.
- Interview: Kenneth Viciana, Equifax on Data Governance – Red Tape or Catalyst? - Mar 14, 2015.
We discuss recommendations for Data Governance policies, advice, Big Data trends, qualities sought in Data Scientists, and more.
- Interview: Josh Hemann, Activision on Why the Tolerance for Ambiguity is Vital - Mar 12, 2015.
We discuss handling bias in data, other data quality concerns, advice, desired qualities, and more.
- Interview: Slava Akmaev, Berg on Challenges in Transitioning Analytics to Clinical Utility - Mar 10, 2015.
We discuss Analytics use cases, challenges in relating molecular/clinical data to real-life outcomes, Healthcare Analytics trends and more.
- Interview: Lei Shi, ChinaHR.com on Unraveling Insights from Unstructured Data - Mar 7, 2015.
We discuss challenges in leveraging Big Data, important attributes while profiling employers and job seekers, competitive landscape, desired skills in data scientists and more.
- Interview: Ted Dunning, MapR on Apache Mahout & Technology Landscape in ML - Mar 3, 2015.
We discuss Apache Mahout, its comparison with Spark and H2O, trends, advice, desired qualities in data scientists and more.
- Interview: David Kasik, Boeing on How Visual Analytics is Improving Aviation Safety - Feb 16, 2015.
We discuss data visualization at Boeing, the importance of Visual Analytics, Aviation Safety improvement through Analytics and augmented reality.
- Interview: M.C. Srivas, CTO, MapR on Data Agility – The Next Frontier of Big Data - Feb 12, 2015.
We discuss the competitive differentiation of MapR, challenges in consumerizing Big Data, trends, strategy recommendations, desired skills and more.
- Interview: Phani Nagarjuna, Nuevora on CMO Expectations from Analytics - Feb 9, 2015.
We discuss the value proposition of Nuevora, founding story, CMO expectations from Analytics and the Nuevora nBAAP platform.
- Interview: John Schitka, SAP on The Type of Data Scientists We Need - Jan 24, 2015.
We discuss the focus areas of Big Data strategy at SAP, how SAP is leading the competition, the kind of data scientists we need, advice and more.
- Interview: Amit Sheth, Kno.e.sis on Designing Academic Curriculum for Data Science - Jan 16, 2015.
We discuss curriculum development around Data Science, trends in Big Data arena, qualities sought in students and more.
- Interview: Amit Sheth, Kno.e.sis on Deriving Actionable Insights from Social Data - Jan 15, 2015.
We discuss Twitris—a tool for collective social intelligence, challenges in using social data to get actionable insights during emergency situations, managing Data Variety, and entrepreneurship.
- Interview: Amit Sheth, Kno.e.sis on Deriving Value from Big Data through Smart Data - Jan 14, 2015.
We discuss the definition of Smart Data, how to derive Smart Data from Big Data, maturity assessment for Smart Data pursuit, computing for human experience and Kno.e.sis.
- Interview: Miriah Meyer, Univ. of Utah on the Art and Science of Visualization - Jan 12, 2015.
We discuss insights from the best paper at ACM AVI 2014, increasing interest in visualization, infographics, trends, challenges, advice and more.
- Interview: Sharmila Mulligan, ClearStory Data on Variety & Velocity to be Big Data Priorities - Jan 10, 2015.
We discuss the ClearStory Data’s competitive differentiation, client use case, Big Data trends, advice, desired soft skills in data scientists and more.
- Interview: Ben Werther, CEO, Platfora on Insightful Analytics for Big Data - Dec 30, 2014.
We discuss the challenges in implementing end-to-end solutions for Big Data, Platfora use cases, Big Data trends, advice and more.
- Interview: Ben Werther, CEO, Platfora on Why Big Data Needs Self-Service Tools - Dec 29, 2014.
We discuss the importance of self-service model for Big Data tools, Small Data vs. Big Data, unique advantages of Platfora, key enhancements in Platfora 4.0 and more.
- Interview: Mac Devine, CTO, IBM Cloud on the Conflux of Cloud, IoT & Big Data - Dec 26, 2014.
We discuss the implications of Cloud Speed of technological advancement, significant trends in Internet of Things (IoT), future of cloud computing and more.
- Interview: Mac Devine, CTO, IBM Cloud on the Fast Approaching Perfect Storm - Dec 24, 2014.
We discuss why we should anticipate a technology perfect storm soon, Enterprise IT challenges, distinct capabilities of IBM BlueMix and more.
- Interview: Brian Hampton, SF 49ers on Competitive Edge through Football Analytics - Dec 20, 2014.
We discuss the shortcomings of football analytics, how San Francisco 49ers use analytics, future of football analytics, advice and more.
- KDnuggets Interview: Paul Zikopoulos, IBM on Why Big Data needs Polyglots - Dec 13, 2014.
We discuss why not to focus on a single technology in Big Data, prevalent myths, what IBM & Twitter partnership means for the world, and current state of data governance.
- Interview: Daqing Zhao, Macys.com on Building Effective Data Models for Marketing - Dec 11, 2014.
We discuss the challenges in identifying the fair price of ad media, recommendations for building effective models for online marketing, unique challenges of Mobile channel, selection of Big Data tools, and more.
- Interview: Daqing Zhao, Macys.com on Advanced Analytics for Marketing in the Big Data era - Dec 10, 2014.
We discuss Analytics at Macys.com, comparison of advanced analytics with traditional BI, building data models for scalability, problem of data models becoming quickly obsolete and challenges in customer targeting.
- Interview: Philip Maymin, NYU on How Optical Analytics will Revolutionize Basketball - Nov 21, 2014.
We discuss the emergence of Optical Analytics, its impact on NBA, challenges in integrating Optical Analytics into game strategy, the trade-off of analytical insights vs gut instinct and the impact on fan engagement.
- The Analytics of Digital Transformation, according to TCS - Nov 17, 2014.
Lipika Dey, in this interview before her talk at next month's LT-Accelerate conference, discusses consumer and market analytics and techniques to extract actionable information from text and social media data.
- KDnuggets Exclusive: Marten Mickos, SVP, HP on the Role of Open Source in Cloud industry - Nov 15, 2014.
In an exclusive interview with KDnuggets, Marten talks about HP’s Open Source strategy, evolution of Open Source production model, learning from the success of Open Source in Web, trends and more.
- KDnuggets Exclusive: Marten Mickos, SVP, HP on Why the Future Belongs to “Hybrid Clouds” - Nov 13, 2014.
In an exclusive interview with KDnuggets, Marten talks about the future of Eucalyptus (recently acquired by HP), defines Hybrid Clouds and their importance, and gives some tips for vendor selection.
- SPOTLIGHT: Can Data Science Save Humanity from Mosquitoes and other Deadly Insects? #2 - Oct 9, 2014.
KDnuggets launches Spotlight initiative to bring attention to academic research. The journey begins with Prof. Eamonn Keogh, UCR and his talented student, Yanping Chen, who are applying data mining to save us all from insect-vectored diseases.
- SPOTLIGHT: Can Data Science Save Humanity from Mosquitoes and other Deadly Insects? - Oct 8, 2014.
KDnuggets launches Spotlight initiative to bring attention to academic research. The journey begins with Prof. Eamonn Keogh and his student, Yanping Chen, who are applying data mining to save us all from insect-vectored diseases.
- Interview: Toni Jones, U-Haul on Deriving Business Insights from Social Media - Oct 5, 2014.
We discuss social media strategy at U-Haul, the key drivers of a social media campaign, identifying what data to focus on, important metrics, career advice and more.
- Exclusive Interview: Imran Siddiqi, SAP on Why the Business needs Ambitious Big Data Use Cases - Sep 13, 2014.
We discuss the selection and tracking of use cases, key points for designing a sustainable information architecture, the need for ambitious use cases, SAP's competitive differentiation, and more.
- Interview: Joe Otto, Alpine on Selecting the Right Big Data Vendor - Sep 10, 2014.
We discuss Big Data vendor landscape, key relevant questions, Alpine's competitive differentiation, important qualities sought in data scientists, and more.
- Interview: Joe Otto, Alpine on Why Big Data is all about Empowerment & Collaboration - Sep 9, 2014.
We discuss the story of Alpine Data Labs, the recent recognition of Alpine, effect of YARN, major customer use cases, and challenges in consumerizing Big Data.
- Exclusive Interview: Ajay Bhargava, TCS on the Ideal Analytics Curriculum at Graduate-level - Sep 5, 2014.
We discuss the differences between analytics and Big Data, the evolution of expectations from data science, important qualities desired in data scientists, ideal curriculum for Analytics focused programs, advice and more.