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Chris Stanley

How to Ensure Data Lakes Success | SmartData Collective - 0 views

www.smartdatacollective.com/...how-ensure-data-lakes-success

data analytics datalake azuredatalake

shared by Chris Stanley on 26 Oct 15 - No Cached
  • it enables businesses to have a more unlimited view of data
  • Data lakes are defined as "a massive, easily accessible, centralized repository of large volumes of structured and unstructured data".
  • businesses must have some use cases in mind before constructing a data lake.
  • ...5 more annotations...
  • Oliver likewise suggests that businesses work with data scientists. Data scientists and engineers provide the necessary expertise required to make the data lake a successful data and analytics tool.
  • Configurable Ingestion WorkflowsNew sources of external information will continuously be available. Make sure to have an easy, secure and trackable content ingestion workflow mechanism that can rapidly add these new information into the data lake.
  • Knowledgent states that "without a high-degree of automated and mandatory metadata management, a Data Lake will rapidly become a Data Swamp" and that "attributes like data lineage, data quality, and usage history are vital to usability".
  • Data lakes must be industry-specific to cater to the industry's unique needs.
  • How to Ensure Data Lakes Success
Chris Stanley

How to create effective data visualizations - 0 views

www.citeworld.com/...y-that-wont-confuse-users.html

data visualization english big data

shared by Chris Stanley on 28 Aug 14 - No Cached
  • 5. Enough with the text, already
  • 1. Present data that matter to your audience (and not just you)
  • Data scientists by definition are naturally inquisitive and love to quantify things. That makes them a good fit for the job. The bad news is that they sometimes become a little too enthusiastic about data for data’s sake and will overwhelm their audience with irrelevant information.
  • ...5 more annotations...
  • 2. Tell a story, simply
  • 3. Choose appropriate visualizations
  • 4. Make sure graphics accurately reflect the data
  • "Try to pick a visualization that depicts not only the level of a variable, but puts it in context for how important it is,"
  • Heat maps and bubble charts are a good example of this. You can see how important a particular region or customer or division is because it takes up more space on the map. You can show other attributes of the variables with color -- e.g., red for underperforming, green for doing well. With a visual like this, managers can quickly see where the problem is, and at the same time they can see how important it is."
Chris Stanley

Chart and image gallery: 30+ free tools for data visualization and analysis | Computerw... - 1 views

www.computerworld.com/...isualization-and-analysis.html

visualization data analytics tools

shared by Chris Stanley on 21 Oct 14 - No Cached
  • he chart below originally accompanied our story 22 free tools for data visualization and analysis (April 20, 2011). We're updating it as we cover additional tools, including 8 cool tools for data analysis, visualization and presentation (March 27, 2012) and Six useful JavaScript libraries for maps, charts and other data visualizations (March 6, 2013). Click through to those articles for full tool reviews.
Chris Stanley

Tool for Analyzing Survey Data, Survey Data Analysis Software - DataCracker - 1 views

www.datacracker.com

survey analysis data spss

shared by Chris Stanley on 05 Dec 14 - No Cached
  • mport your data to our survey data analysis software from all major survey programs and file formats. SurveyMonkey SurveyGizmo QuestionPro Qualtrics Survey Analytics Snap Surveys Toluna QuickSurveys Super Simple Survey SPSS (.sav) Triple-S (.xml or .sss) IBM SPSS Data Model (.mdd) Excel (.xls or .xlsx) CSV (.csv)
Chris Stanley

Valley heavyweight Vinod Khosla says replacing doctors with data crunchers is good medi... - 0 views

venturebeat.com/...ata-crunchers-is-good-medicine

big data analytics healthcare

shared by Chris Stanley on 27 Aug 14 - No Cached
  • “Humans are not good when 500 variables affect a disease. We can handle three to five to seven, maybe,” he said. “We are guided too much by opinions, not by statistical science.”
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