- Cloud Data Warehouse is The Future of Data Storage - Jan 12, 2021.
Today, cloud data storage accounts for 45% of all enterprise data and by Q2 2021, that number could grow to 53%. Now is the time to embrace cloud than now.
- Meet whale! The stupidly simple data discovery tool - Dec 31, 2020.
Finding data and understanding its meaning represents the traditional "daily grind" of a Data Scientist. With whale, the new lightweight data discovery, documentation, and quality engine for your data warehouse that is under development by Dataframe, your data science team will more efficiently search data and automate its data metrics.
- Feature Store vs Data Warehouse - Dec 22, 2020.
A feature store is a data warehouse of features for machine learning. Differently from a data warehouse, it is dual-database: one serving features at low latency to online applications and another storing large volumes of features. Learn how Data Scientists leverage this capability in production-deployed models.
- 4 Myths of Big Data and 4 Ways to Improve with Deep Data - Jan 9, 2019.
There is a fundamental misconception that bigger data produces better machine learning results. However bigger data lakes / warehouses won’t necessarily help to discover more profound insights. It is better to focus on data quality, value and diversity not just size. "Deep Data" is better than Big Data.
- From Insights to Value in 90 Minutes – with Snowflake, July 12 Webinar - Jul 2, 2018.
Learn How to Accelerate Data Warehouse Modernization at a Low Cost.
- Choosing Between Modern Data Warehouses - Jun 28, 2018.
Most of the modern data warehouse solutions are designed to work with raw data. It allows to re-transform data on the fly without a need to re-ingest your data stored in a warehouse.
- Why Data and Infrastructure are key to determining Customer Intent,
May 31 Webinar - May 22, 2018.
Join Yieldmo, an advertising technology company and learn how Snowflake and Looker unleashed the potential of their mobile ad engagement data and drove more impactful marketing for their clients.
- ETL vs ELT: Considering the Advancement of Data Warehouses - May 22, 2018.
The traditional concept of ETL is changing towards ELT – when you’re running transformations right in the data warehouse. Let’s see why it’s happening, what it means to have ETL vs ELT, and what we can expect in the future.
- Is a Single Version of Truth Possible?
May 16 Webinar - May 10, 2018.
The data warehouse promised to deliver a single version of truth. But skeptics abound, saying a single version of truth is a mirage and not necessary. Join this webinar and learn from experts debating this question.
- Modernize your data infrastructure with Looker + AWS - Apr 25, 2018.
Learn how you can improve performance and optimize resources using Looker + AWS and Amazon Redshift with Looker extensive pre-built analytics models for AWS data. As a bonus, we will give 1K credit towards AWS data warehouse.
- Get a headstart with Looker and 1K credits for your AWS data warehouse - Apr 11, 2018.
Looker partnered with AWS to offer, for a limited time, a free trial of Looker with a bonus of $1,000 credits towards your AWS data warehouse.
- Get a headstart with Looker – and $1,000 credits towards your AWS data warehouse - Apr 2, 2018.
Looker has partnered with AWS to offer, for a limited time, a free trial of Looker with a bonus of $1,000 credits towards your AWS data warehouse.
- How data science can improve retail - Mar 1, 2018.
We’re going to take a look at a few surprising ways that data science can increase your sales, both offline and online.
- Are Data Lakes Fake News? - Sep 6, 2017.
The quick answer is yes, and the biggest problem is that the term “Data Lakes” has been overloaded by vendors and analysts with different meanings, resulting in an ill-defined and blurry concept.
- Hadoop as a Data Warehouse: Cracking the Code with Kudu - Jun 15, 2017.
Here we discuss problems behind replacing an existing Data Warehouse with Hadoop and available solutions to make this happen. Lets see how.
- 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.