KDnuggets Interview: Amr Awadallah, CTO & Co-founder, Cloudera on the Need for Self-Service Analytics
We discuss the importance of enabling self-service analytics, partnership with Cask, Big Data vendor selection and competitive landscape.
on Jun 30, 2015 in Acquisitions, Amr Awadallah, Analytics, Cask, Cloudera, Hortonworks, Interview, MapR, Self-service, Vendors, Xplain.io
Nine Laws of Data Mining, part 2
The second group data mining laws includes: There are always patterns, Data mining amplifies perception in the business domain, Prediction increases information locally by generalisation, Value law, Law of Change. Tom Khabaza explains.
on Jun 30, 2015 in CRISP-DM, Data Mining, Tom Khabaza
KDnuggets Interview: Amr Awadallah, CTO & Co-founder, Cloudera on the Future of Information Architecture Design
We discuss Cloudera’s achievements, story behind the name ‘Cloudera’, CTO role, and key attributes of information architecture designed for future.
on Jun 29, 2015 in Amr Awadallah, Cloudera, Hadoop, Information Management, Interview, Performance, Success
Nine Laws of Data Mining, part 1
Tom Khabaza, one of the authors of the Clementine data mining workbench and of CRISP-DM methodology for data mining process, proposes and explains 9 laws of data mining.
on Jun 29, 2015 in CRISP-DM, Data Mining, Tom Khabaza
Big Data Big Impact on the Future of Advertising
Big data is ready to tack advertisement industry to a new height. Here, we captured how big data will shape the advertising in the future, its challenges and opportunities.
on Jun 26, 2015 in Big Data, Online advertising, Privacy
Data Science and Mobile Devices: Joined at the Hip
As number of wearable and IoT devices have soared, there is a new big data market emerging at horizon. Here, we have scratched the surface of this giant and got few connections between mobile devices and data science.
on Jun 25, 2015 in Data Science, IoT, Mobile, Mobility
Interview: Anil Gadre, MapR on 3 Keys for Big Data Success: Reliability, Security, & Scalability
We discuss the origin of Apache Myriad, state of security in Big Data, MapR Quick Start Solutions, Hadoop vendor selection criteria, and more.
on Jun 24, 2015 in Anil Gadre, Future, Hadoop, Interview, MapR, Security, Success, Trends, Vendors
Interview: Anil Gadre, MapR on What it takes to Automate Data-to-Action?
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.
on Jun 23, 2015 in Anil Gadre, Business Analytics, Decision Making, Hadoop, Interview, MapR, Realtime Analytics, Teradata
10 reasons why I love data and analytics
As data science getting more and more traction in all the major industries. So, in this new, exciting and challenging field there are lots of opportunities. Here are few reasons why you should be a part of this.
By Paul Balm on Jun 22, 2015 in Big Data, Data Science, Decision Making, Predictive Analytics
Spark Summit 2015 San Francisco – Day 2 Keynote Highlights
Highlights from keynote speeches delivered by various eminent big data technology leaders from industry and academia at Spark Summit 2015 Conference held in San Francisco.
on Jun 19, 2015 in Apache Spark, AWS, Baidu, CIA, Cloudera, Databricks, Intel, Spark SQL, Toyota
I’m a data scientist – mind if I do surgery on your heart?
If I walked into an operating room and said I'm going to start dabbling in surgery I would be immediately thrown out. But people do that with statistics and data analysis all the time.
on Jun 18, 2015 in Data Analysis, Data Scientist, Healthcare, HealthKit, Medical
Spark Summit 2015 San Francisco – Day 1 Keynote Highlights
Highlights from keynote speeches delivered by various eminent big data technology leaders from industry and academia at Spark Summit 2015 Conference held in San Francisco.
on Jun 17, 2015 in Apache Spark, Conference, Databricks, Highlights, Hortonworks, IBM, MapR, Matei Zaharia, NASA
Interview: Joseph Babcock, Netflix on Curiosity and Courage – Key for Success in Data Science
We discuss discovery vs. personalization, advice, trends, desired skills in data scientists, and more.
on Jun 17, 2015 in Advice, Career, Hiring, Interview, Joseph Babcock, Metrics, Netflix, Trends
Interview: Joseph Babcock, Netflix on Genie, Lipstick, and Other In-house Developed Tools
We discuss role of analytics in content acquisition, data architecture at Netflix, organizational structure, and open-source tools from Netflix.
on Jun 16, 2015 in Data Science, ETL, In-house, Interview, Joseph Babcock, Netflix, Open Source, Tools
Interview: Joseph Babcock, Netflix on Discovery and Personalization from Big Data
We discuss the steps involved in Discovery process at Netflix, impact due to multitude of devices, system generated logs, and surprising insights.
on Jun 15, 2015 in Experimentation, Insights, Interview, Joseph Babcock, Knowledge Discovery, Netflix, Personalization
Is Analytics Career Right for You?
An analytical way to decide whether you should pursue a career in analytics. We shared some economic ways to getting started and mind-set required for entering into this exciting field.
on Jun 12, 2015 in Advice, Career, Data Science Skills, Skills
Cognitive Computing: Solving the Big Data Problem?
With a shortage of data scientists, what are the alternatives for making sense of Big Data? We examine Cognitive Computing, its strengths, and how it can fit into the current Big Data landscape.
on Jun 12, 2015 in Cognitive Computing, DeepMind, Google, IBM Watson, Qualcomm, Rick Delgado
Interview: Beth Smith, General Manager of the IBM Analytics Platform business, on Analytics, Hadoop, Spark
We discuss coming Analytics surprises, what has changed, Open Source, Hadoop, Apache Spark, Open Data Platform, new analytics roles, IBM resources for analytics educations, and more.
on Jun 12, 2015 in Apache Spark, Beth Smith, Hadoop, IBM
Interview: Ranjan Sinha, eBay on Winner Insights from International Sorting Competitions
We discuss advancements in the field of Personalization, lessons from winning sorting competitions, Data Science trends, career advice, and more.
on Jun 10, 2015 in Advice, Career, Competition, eBay, Insights, Interview, Personalization, Ranjan Sinha, Recommendation, Trends
Interview: Ranjan Sinha, eBay on Advanced Hadoop Cluster Management through Predictive Modeling
We discuss categorization of e-commerce analytics, opportunities/ challenges of Big Data, Astro predictive model for Hadoop cluster management, and Apache Kylin.
on Jun 9, 2015 in Apache Hive, Apache Kylin, Astro, Customer Experience, eBay, Ecommerce, Hadoop, Interview, Predictive Modeling, Ranjan Sinha
Interview: James Taylor, Salesforce on Phoenix + HBase – The Future of Big Data
We discuss the advantages of Phoenix, upcoming features, soon coming-up support for transactions, trends, advice, and more.
on Jun 6, 2015 in Apache Phoenix, Distributed Systems, Future, HBase, Interview, James Taylor, Salesforce
Interview: James Taylor, Salesforce on Apache Phoenix – RDBMS for Big Data
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.
on Jun 5, 2015 in Apache Phoenix, HBase, Interview, James Taylor, Open Source, Performance, RDBMS, Salesforce
Love, Sex and Predictive Analytics
Here, we are trying to understand the working mechanisms of dating sites, algorithms used and role of predictive analytics while matchmaking. We have also gleaned some interesting analytical insights from them.
on Jun 4, 2015 in Love, Match.com, OkCupid, Online Dating, Predictive Analytics, Recommendation, Tinder
Interview: Sheridan Hitchens, Auction.com on Data Science Evolution from a Nerdy Hobby to a Strategic Priority
We discuss the evolution of Data Science expectations, Data Science as a career, advice, and more.
on Jun 4, 2015 in Advice, Auction, Career, Data Science, Future, Interview, Sheridan Hitchens, Skills
Data Mining and Predictive Analytics Glossary
Here, we have collected definitions of common terminologies used in data science and big data.
on Jun 3, 2015 in Algolytics, Data Mining, Data Science Jargon, Glossary
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