- Webinar: Athena Health “Unbreaks” Health Care by Modernizing their Data Stack, Feb 28 - Feb 17, 2017.
With a new Snowflake data warehouse and Looker data platform on top, data analysts at athenahealth are delivering data to more people, and improving patient experience in the US healthcare system. Register and learn how.
- Big Data Key Terms, Explained - Aug 11, 2016.
Just getting started with Big Data, or looking to iron out the wrinkles in your current understanding? Check out these 20 Big Data-related terms and their concise definitions.
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- UF Health Shands Hospital: Decision Support Analyst, Data Warehousing/Reporting Infrastructure - Jul 27, 2016.
Design, develop and maintain the data warehouse and/or semantic reporting layer for UF Health Shands, including delivery of BI information to the entire organization.
- Take a Risk Free Hadoop Ride. Save up to 80% cost and offload time. - Jul 14, 2016.
The Impetus Data Warehouse Workload Migration product is a proven, cost-effective, and low-risk solution to offload traditional data warehouse to Big Data warehouse. Contact us for a proof-of-concept.
- Data Lake Plumbers: Operationalizing the Data Lake - Feb 18, 2016.
Gain insight into data lakes, their benefits, when they are appropriate, and how to operationalize them. How do they compare to the data warehouse?
- Hadoop and Big Data: The Top 6 Questions Answered - Jan 22, 2016.
6 questions surrounding Hadoop and Big Data are posed and answered, including those related to implementation, management, and practical uses. Find out where Hadoop currently sits in the world of Big Data.
- Webinar: 5 tips to get more out of Data Lakes, Dec 16 - Dec 1, 2015.
Learn valuable tips to help optimize Big Data for agility and speed to insight; improve data accessibility, without the limitations of data warehouses, and prevent data sources from becoming data silos.
- Data Lake vs Data Warehouse: Key Differences - Sep 29, 2015.
We hear lot about the data lakes these days, and many are arguing that a data lake is same as a data warehouse. But in reality, they are both optimized for different purposes, and the goal is to use each one for what they were designed to do.
- Top KDnuggets tweets, Jul 7-13: Deep Learning and the Triumph of Empiricism - Jul 14, 2015.
Deep Learning and the Triumph of Empiricism; What can Hadoop do that my data warehouse cant?; Emacs for Data Science; Dataiku DataScience Studio - intuitive solution.
- 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.
- TDWI Orlando – The Premier Education Conference for BI, DW, Big Data, Data Analytics – Savings Extended - Nov 11, 2014.
With over 45 courses on the full agenda, TDWI Orlando has what you need to succeed with your data and analytics projects! Savings extended - use priority code OR63.
- TDWI Orlando, Dec 7-12, Premier Education Event for BI, Big Data and Analytics - Oct 16, 2014.
Plan your week with the complete 6-day agenda, including course descriptions, keynotes, exhibit hall times, networking events, and BI certification opportunities.
- ASE International Conference on Big Data Science 2014: Highlights from Workshops - Jul 31, 2014.
Highlights from the presentations by Data Science leaders from MIT, Georgia Tech, Microsoft Research and CUHK during workshops at ASE Conference on Big Data Science 2014 held in Stanford University.
- Dear CIO, what you have is NOT a Data Lake - Jul 17, 2014.
Data Lakes are often the ideal structure of a company's big data, but the reality is that data is often split into data puddles. Xurmo seeks to eliminate this by integrating Data Virtualization into the Data Lake.
- Top stories for Jun 1-7 - Jun 8, 2014.
New Poll: Analytics, Data Mining, Data Science Software Used? OpenNN, An Open Source Library For Neural Networks; Data Lakes vs Data Warehouses; Stanford University: Data Analyst.
- Data Lakes vs Data Warehouses - Jun 7, 2014.
Data Warehouses, traditionally popular for business intelligence tasks, are being replaced by less-structured Data Lakes which allow more flexibility.