• "Druid: Powering Interactive Data Applications at Scale" by Fangjin Yang

    Cluster computing frameworks such as Hadoop or Spark are tremendously beneficial in processing and deriving insights from data. However, long query latencies make these frameworks sub-optimal choices to power interactive applications. Organizations frequently rely on dedicated query layers, such as relational databases and key/value stores, for faster query latencies, but these technologies suffer many drawbacks for analytic use cases. In this session, we discuss using Druid for analytics, and why the architecture is well suited to power analytic applications. User facing applications are replacing traditional reporting interfaces as the preferred means for organizations to derive value from their datasets. In order to provide an interactive user experience, user interactions with analyti...

    published: 17 Sep 2016
  • Druid Interactive Queries Meet Real-Time Data Eric Tschetter and Danny Yuan

    On-the-fly aggregation with human-time (or "interactive") queries against fresh, at-the-moment data represents a growing trend. Many newly announced systems are starting to provide interactive queries on batched data streams. This talk discusses how Druid allows users to have interactive queries on real-time data at scale; we feature a case study with Netflix leveraging Druid to obtain at-the-moment insight as it ingests over two terabytes per hour.

    published: 05 Apr 2013
  • Interactive Data Analytics with Couchbase N1QL at Nielsen – Couchbase Connect 2015

    In this session we’ll discuss how Couchbase’s query language, N1QL provided Nielsen with an interactive querying capability that significantly increased our ability to gather meaningful insights into stored client data. In this session, you will learn how we gather those insights and interact with data analytics while leveraging SQL for JSON, N1QL. For context, Nielsen’s Answers on Demand (AOD) services deliver ratings data and other information for businesses in more than 100 countries. With the inflow of massive volumes of data and the requirement to deliver highly targeted results for clients, the ability to sift through datasets quickly and effectively is critical. The AOD services need to provide powerful analytics and reporting capabilities – essentially aggregations on the fly – thr...

    published: 17 Jun 2015
  • RINSE: Interactive Data Series Exploration

    URL: http://daslab.seas.harvard.edu/rinse People: Kostas Zoumpatianos (University of Trento), Stratos Idreos (Harvard University), Themis Palpanas (Paris Descartes University) Information: ------------------ Numerous applications continuously produce big amounts of data series, and in several time critical scenarios analysts need to be able to query these data as soon as they become available, which is not currently possible with the state-of-the-art indexing methods and for very large data series collections. We develop the first adaptive data series indexing mechanism, called ADS+, specifically tailored to solve the problem of indexing and querying very large data series collections. The main idea is that instead of building the complete index over the complete data set up-front a...

    published: 11 Jun 2015
  • Discover HDP 2.1: Interactive SQL Query in Hadoop with Apache Hive

    In February 2013, the open source community launched the Stinger Initiative to improve speed, scale and SQL semantics in Apache Hive. After thirteen months of constant, concerted collaboration (and more than 390,000 new lines of Java code) Stinger is complete with Hive 0.13. In this 30-minute webinar, Carter Shanklin, Hortonworks director of product management, and Owen O'Malley, Hortonworks co-founder and committer to Apache Hive, discuss how Hive enables interactive query using familiar SQL semantics. Carter and Owen present an overview of Hive 0.13, followed by a brief demo, with Q & A at the end.

    published: 15 May 2014
  • Interactive Data Analysis

    Data analysis is a complex process with frequent shifts among data formats and models, and among textual and graphical media. We are investigating how to better support this lifecycle of analysis by identifying critical bottlenecks and developing new methods at the intersection of data visualization, machine learning and computer systems. Can we empower users to transform and clean data without programming? Can we design scalable representations and systems to visualize and query big data in real-time? How might we enable domain experts to guide machine learning methods to produce better models? I will present selected projects that attempt to address these challenges and introduce new tools for interactive visual analysis. Jeffrey Heer Associate Professor UW Computer Science & Engineer...

    published: 20 Nov 2013
  • Visualization and Interactive Data Analysis - DataEDGE 2013

    DataEDGE 2013 - http://dataedge.ischool.berkeley.edu Visualization and Interactive Data Analysis Jeffrey Heer, Assistant Professor of Computer Science, Stanford University Data analysis constitutes a complex sensemaking process with frequent representational shifts among data formats and models, and among textual and graphical media. This process is both iterative and interactive, with analysts moving back and forth among phases of analysis and exercising domain expertise. We are investigating how to better support this analytic lifecycle by identifying critical bottlenecks and developing new interactive systems for data analysis. Our research agenda integrates perspectives from human-computer interaction, visualization, systems and machine learning. Can we empower users to transform an...

    published: 15 Jun 2013
  • Interactive Data Visualization with Power View

    In this session, we take a deep dive into Power View, Microsoft's interactive data visualization experience. Through some cool demos, learn how to create beautiful, interactive Power View reports while getting a tour of the product's features. Also, learn about the architecture of Power View and related components, and about the different flavors of Power View (Power BI in Office 365 vs. on-premise, Excel desktop vs. Excel Web App vs. Power View Web App) and their differences. If you're eager to gain a deeper understanding of Power View, don't miss this session!

    published: 20 May 2014
  • IMF STA Data Portal Query Tutorial

    This tutorial walks through the Query tool, a powerful interactive feature of the IMF Data Portal that allows users to build, export and share custom outputs and visualizations. IMF Data Help: http://datahelp.imf.org/

    published: 24 Jun 2015
  • iSPARQL & Linked Data Query Demo 1

    Interactive SPARQL and Linked Data

    published: 03 Oct 2008
  • An Interactive Visual Query Environment for Exploring Data

    Direct manipulation of visualizations is a powerful technique for performing exploratory data operations such as navigation, aggregation, and filtering. Its immediacy facilitates rapid, incremental, and reversible forays into the data. However it does not provide for reuse or modification of exploration sessions. This paper describes a visual query language, VQE, that adds these capabilities to a direct manipulation exploration environment called Visage. Queries and visualizations are dynamically linked: operations on either one immediately update the other, in contrast to the feedforward sequence of database query followed by visualization of results common in traditional systems. Accompanies paper at http://www.cs.cmu.edu/~sage/Papers/UIST97/UIST97.html

    published: 01 Jun 2014
  • Q-Sensei Interactive Query Builder

    Q-Sensei´s Interactive Query Builder provides an intuitive interface that enables you to create complex queries for your data. www.qsensei.com Music: Carefree Kevin MacLeod (incompetech.com) Licensed under Creative Commons: By Attribution 3.0 License http://creativecommons.org/licenses/by/3.0/

    published: 11 Apr 2017
  • Interactive Data Analysis - Jeffrey Heer - May 23, 2013

    This talk is part of the symposium, "Data Visualization from Data to Discovery: Art Center + Caltech + JPL", May 23, 2013 | Beckman Auditorium | Caltech, Pasadena, CA, USA | http://www.hi.jpl.nasa.gov/datavis Interactive Data Analysis Data analysis is a complex process with frequent shifts among data formats and models, and among textual and graphical media. We are investigating how to better support this lifecycle of analysis by identifying critical bottlenecks and developing new methods at the intersection of data visualization, machine learning and computer systems. Can we empower users to transform and clean data without programming? Can we design scalable representations and systems to visualize and query big data in real-time? How might we enable domain experts to guide machine lea...

    published: 12 Jun 2013
  • Create a Query Based on an Excel or Text File

    Learn how to directly insert data coming from an Excel file or a text file in Interactive Analysis. This data can either enrich an existing document or be analyzed to find new information.

    published: 18 Nov 2010
  • Create a query based on an Excel file: SAP BusinessObjects Web Intelligence 4.0

    In this video, we will create a new Web Intelligence document based on a local Microsoft Excel spreadsheet. Visit us at http://www.sap.com/LearnBI to view our full catalog of interactive SAP BusinessObjects BI Suite tutorials.

    published: 06 Jan 2015
  • Making Sense of Temporal Queries with Interactive Visualization

    To help analysts better understand temporal queries, we developed StreamTrace, an interactive visualization tool that breaks down how a temporal query processes a given dataset, step-by-step. We demonstrate that StreamTrace can help users to verify that queries behave as expected and to isolate the regions of a query that may be causing unexpected results. http://research.microsoft.com/

    published: 06 Jun 2016
"Druid: Powering Interactive Data Applications at Scale" by Fangjin Yang

"Druid: Powering Interactive Data Applications at Scale" by Fangjin Yang

  • Order:
  • Duration: 45:01
  • Updated: 17 Sep 2016
  • views: 4803
videos
Cluster computing frameworks such as Hadoop or Spark are tremendously beneficial in processing and deriving insights from data. However, long query latencies make these frameworks sub-optimal choices to power interactive applications. Organizations frequently rely on dedicated query layers, such as relational databases and key/value stores, for faster query latencies, but these technologies suffer many drawbacks for analytic use cases. In this session, we discuss using Druid for analytics, and why the architecture is well suited to power analytic applications. User facing applications are replacing traditional reporting interfaces as the preferred means for organizations to derive value from their datasets. In order to provide an interactive user experience, user interactions with analytic applications must complete in an order of milliseconds. To meet these needs, organizations often struggle with selecting a proper serving layer. Many serving layers are selected because of their general popularity, without understanding the possible architecture limitations. Druid is an analytics data store designed for analytic (OLAP) queries on event data. It draws inspiration from Google's Dremel, Google's PowerDrill, and search infrastructure. Many large technology companies are switching to Druid for analytics, and we will cover why the technology is a good fit for its intended use cases.
https://wn.com/Druid_Powering_Interactive_Data_Applications_At_Scale_By_Fangjin_Yang
Druid Interactive Queries Meet Real-Time Data Eric Tschetter and Danny Yuan

Druid Interactive Queries Meet Real-Time Data Eric Tschetter and Danny Yuan

  • Order:
  • Duration: 44:11
  • Updated: 05 Apr 2013
  • views: 6332
videos
On-the-fly aggregation with human-time (or "interactive") queries against fresh, at-the-moment data represents a growing trend. Many newly announced systems are starting to provide interactive queries on batched data streams. This talk discusses how Druid allows users to have interactive queries on real-time data at scale; we feature a case study with Netflix leveraging Druid to obtain at-the-moment insight as it ingests over two terabytes per hour.
https://wn.com/Druid_Interactive_Queries_Meet_Real_Time_Data_Eric_Tschetter_And_Danny_Yuan
Interactive Data Analytics with Couchbase N1QL at Nielsen – Couchbase Connect 2015

Interactive Data Analytics with Couchbase N1QL at Nielsen – Couchbase Connect 2015

  • Order:
  • Duration: 36:03
  • Updated: 17 Jun 2015
  • views: 1480
videos
In this session we’ll discuss how Couchbase’s query language, N1QL provided Nielsen with an interactive querying capability that significantly increased our ability to gather meaningful insights into stored client data. In this session, you will learn how we gather those insights and interact with data analytics while leveraging SQL for JSON, N1QL. For context, Nielsen’s Answers on Demand (AOD) services deliver ratings data and other information for businesses in more than 100 countries. With the inflow of massive volumes of data and the requirement to deliver highly targeted results for clients, the ability to sift through datasets quickly and effectively is critical. The AOD services need to provide powerful analytics and reporting capabilities – essentially aggregations on the fly – through an on-demand big data platform. We at Nielsen turned to Couchbase to persist client report definitions, selections, and cache enabling us to sidestep many of the limitations of relational databases operating in a multitenant environment. The Couchbase solution delivered a 50 percent boost in response time by pre-indexing metadata and gave us the ability to query against the index or target specific documents with N1QL. Speakers: Arvind Jade, Architect Lead, Nielsen Govindarajan Raghunathapuram, Solutions Architect, Nielsen Slideshare: http://www.slideshare.net/Couchbase/unleash-the-power-of-couchbase-throughn1-ql-nickel Visit our website for more information https://www.couchbase.com/
https://wn.com/Interactive_Data_Analytics_With_Couchbase_N1Ql_At_Nielsen_–_Couchbase_Connect_2015
RINSE: Interactive Data Series Exploration

RINSE: Interactive Data Series Exploration

  • Order:
  • Duration: 2:42
  • Updated: 11 Jun 2015
  • views: 604
videos
URL: http://daslab.seas.harvard.edu/rinse People: Kostas Zoumpatianos (University of Trento), Stratos Idreos (Harvard University), Themis Palpanas (Paris Descartes University) Information: ------------------ Numerous applications continuously produce big amounts of data series, and in several time critical scenarios analysts need to be able to query these data as soon as they become available, which is not currently possible with the state-of-the-art indexing methods and for very large data series collections. We develop the first adaptive data series indexing mechanism, called ADS+, specifically tailored to solve the problem of indexing and querying very large data series collections. The main idea is that instead of building the complete index over the complete data set up-front and querying only later, we interactively and adaptively build parts of the index, only for the parts of the data on which the users pose queries. The net effect is that instead of waiting for extended periods of time for the index creation, users can immediately start exploring the data series. In this demonstration we present RINSE, a system that allows users to experience the benefits of ADS+ through an intuitive web interface. It allows them to explore large datasets and find patterns of interest, using nearest neighbor search. Users can either draw queries using a mouse or touch screen or they can select them from other data series collections. RINSE can scale to large data sizes, while drastically reducing the data to query delay: by the time state-of-the-art indexing techniques finish indexing 1 billion data series (and before answering even a single query), adaptive data series indexing can already answer $3*10^5$ queries.
https://wn.com/Rinse_Interactive_Data_Series_Exploration
Discover HDP 2.1: Interactive SQL Query in Hadoop with Apache Hive

Discover HDP 2.1: Interactive SQL Query in Hadoop with Apache Hive

  • Order:
  • Duration: 27:56
  • Updated: 15 May 2014
  • views: 5906
videos
In February 2013, the open source community launched the Stinger Initiative to improve speed, scale and SQL semantics in Apache Hive. After thirteen months of constant, concerted collaboration (and more than 390,000 new lines of Java code) Stinger is complete with Hive 0.13. In this 30-minute webinar, Carter Shanklin, Hortonworks director of product management, and Owen O'Malley, Hortonworks co-founder and committer to Apache Hive, discuss how Hive enables interactive query using familiar SQL semantics. Carter and Owen present an overview of Hive 0.13, followed by a brief demo, with Q & A at the end.
https://wn.com/Discover_Hdp_2.1_Interactive_Sql_Query_In_Hadoop_With_Apache_Hive
Interactive Data Analysis

Interactive Data Analysis

  • Order:
  • Duration: 28:06
  • Updated: 20 Nov 2013
  • views: 211
videos
Data analysis is a complex process with frequent shifts among data formats and models, and among textual and graphical media. We are investigating how to better support this lifecycle of analysis by identifying critical bottlenecks and developing new methods at the intersection of data visualization, machine learning and computer systems. Can we empower users to transform and clean data without programming? Can we design scalable representations and systems to visualize and query big data in real-time? How might we enable domain experts to guide machine learning methods to produce better models? I will present selected projects that attempt to address these challenges and introduce new tools for interactive visual analysis. Jeffrey Heer Associate Professor UW Computer Science & Engineering
https://wn.com/Interactive_Data_Analysis
Visualization and Interactive Data Analysis - DataEDGE 2013

Visualization and Interactive Data Analysis - DataEDGE 2013

  • Order:
  • Duration: 53:53
  • Updated: 15 Jun 2013
  • views: 2443
videos
DataEDGE 2013 - http://dataedge.ischool.berkeley.edu Visualization and Interactive Data Analysis Jeffrey Heer, Assistant Professor of Computer Science, Stanford University Data analysis constitutes a complex sensemaking process with frequent representational shifts among data formats and models, and among textual and graphical media. This process is both iterative and interactive, with analysts moving back and forth among phases of analysis and exercising domain expertise. We are investigating how to better support this analytic lifecycle by identifying critical bottlenecks and developing new interactive systems for data analysis. Our research agenda integrates perspectives from human-computer interaction, visualization, systems and machine learning. Can we empower users to transform and integrate data without programming? Can we design scalable systems and representations to interactively query and visualize data? How might we enable domain experts to guide machine learning methods to produce better models? I will present selected projects that attempt to address these challenges and create new interfaces, algorithms and models that enable analytic reasoning with complex data.
https://wn.com/Visualization_And_Interactive_Data_Analysis_Dataedge_2013
Interactive Data Visualization with Power View

Interactive Data Visualization with Power View

  • Order:
  • Duration: 1:15:53
  • Updated: 20 May 2014
  • views: 62013
videos
In this session, we take a deep dive into Power View, Microsoft's interactive data visualization experience. Through some cool demos, learn how to create beautiful, interactive Power View reports while getting a tour of the product's features. Also, learn about the architecture of Power View and related components, and about the different flavors of Power View (Power BI in Office 365 vs. on-premise, Excel desktop vs. Excel Web App vs. Power View Web App) and their differences. If you're eager to gain a deeper understanding of Power View, don't miss this session!
https://wn.com/Interactive_Data_Visualization_With_Power_View
IMF STA Data Portal Query Tutorial

IMF STA Data Portal Query Tutorial

  • Order:
  • Duration: 4:23
  • Updated: 24 Jun 2015
  • views: 6298
videos
This tutorial walks through the Query tool, a powerful interactive feature of the IMF Data Portal that allows users to build, export and share custom outputs and visualizations. IMF Data Help: http://datahelp.imf.org/
https://wn.com/Imf_Sta_Data_Portal_Query_Tutorial
iSPARQL & Linked Data Query Demo 1

iSPARQL & Linked Data Query Demo 1

  • Order:
  • Duration: 3:26
  • Updated: 03 Oct 2008
  • views: 991
videos https://wn.com/Isparql_Linked_Data_Query_Demo_1
An Interactive Visual Query Environment for Exploring Data

An Interactive Visual Query Environment for Exploring Data

  • Order:
  • Duration: 5:42
  • Updated: 01 Jun 2014
  • views: 65
videos
Direct manipulation of visualizations is a powerful technique for performing exploratory data operations such as navigation, aggregation, and filtering. Its immediacy facilitates rapid, incremental, and reversible forays into the data. However it does not provide for reuse or modification of exploration sessions. This paper describes a visual query language, VQE, that adds these capabilities to a direct manipulation exploration environment called Visage. Queries and visualizations are dynamically linked: operations on either one immediately update the other, in contrast to the feedforward sequence of database query followed by visualization of results common in traditional systems. Accompanies paper at http://www.cs.cmu.edu/~sage/Papers/UIST97/UIST97.html
https://wn.com/An_Interactive_Visual_Query_Environment_For_Exploring_Data
Q-Sensei Interactive Query Builder

Q-Sensei Interactive Query Builder

  • Order:
  • Duration: 2:24
  • Updated: 11 Apr 2017
  • views: 56
videos
Q-Sensei´s Interactive Query Builder provides an intuitive interface that enables you to create complex queries for your data. www.qsensei.com Music: Carefree Kevin MacLeod (incompetech.com) Licensed under Creative Commons: By Attribution 3.0 License http://creativecommons.org/licenses/by/3.0/
https://wn.com/Q_Sensei_Interactive_Query_Builder
Interactive Data Analysis - Jeffrey Heer - May 23, 2013

Interactive Data Analysis - Jeffrey Heer - May 23, 2013

  • Order:
  • Duration: 1:01:24
  • Updated: 12 Jun 2013
  • views: 11236
videos
This talk is part of the symposium, "Data Visualization from Data to Discovery: Art Center + Caltech + JPL", May 23, 2013 | Beckman Auditorium | Caltech, Pasadena, CA, USA | http://www.hi.jpl.nasa.gov/datavis Interactive Data Analysis Data analysis is a complex process with frequent shifts among data formats and models, and among textual and graphical media. We are investigating how to better support this lifecycle of analysis by identifying critical bottlenecks and developing new methods at the intersection of data visualization, machine learning and computer systems. Can we empower users to transform and clean data without programming? Can we design scalable representations and systems to visualize and query big data in real-time? How might we enable domain experts to guide machine learning methods to produce better models? Jeffrey Heer presents selected projects that attempt to address these challenges and introduce new tools for interactive visual analysis. Jeffrey Heer is an Assistant Professor of Computer Science at Stanford University, where he works on human-computer interaction, visualization and social computing. His research investigates the perceptual, cognitive and social factors involved in making sense of large data collections, resulting in new interactive systems for visual analysis and communication. The visualization tools developed by his lab (D3, Protovis, Flare, Prefuse) are used by researchers, companies and thousands of data enthusiasts around the world. His group has received Best Paper and Honorable Mention awards at the premier venues in Human-Computer Interaction and Information Visualization (ACM CHI, ACM UIST, IEEE InfoVis, IEEE VAST). In 2009 Jeff was named to MIT Technology Review's TR35; in 2012 he was named a Sloan Foundation Research Fellow. He holds BS, MS and PhD degrees in Computer Science from the University of California, Berkeley. About the symposium: Nearly every scientific and engineering endeavor faces a fundamental challenge to see and extract insights from data. Effective Data Science and Visualization can lead to new discoveries. Together, we at Caltech, NASA JPL, and Art Center represent the same convergence of science, engineering and design that drives new Big Data-powered discovery. On May 23, 2013, industry leaders visited Pasadena for a series of talks to inspire, unite and challenge our community to re-examine our practices, and our perspectives. Guests included: * Fernanda Viégas & Martin Wattenberg | Co-leaders, Google Data Visualization Group * Jer Thorp | Co-founder, The Office for Creative Research * Golan Levin | Director, Carnegie Mellon Studio for Creative Inquiry * Eric Rodenbeck | Founder, Stamen Design * Jeff Heer | Assistant Professor, Stanford University * Anja-Silvia Goeing | Privatdozent, University of Zurich and Lecturer of History and History of Science, Caltech See http://www.hi.jpl.nasa.gov/datavis for more information. Produced in association with Caltech Academic Media Technologies. © 2013 California Institute of Technology.
https://wn.com/Interactive_Data_Analysis_Jeffrey_Heer_May_23,_2013
Create a Query Based on an Excel or Text File

Create a Query Based on an Excel or Text File

  • Order:
  • Duration: 1:36
  • Updated: 18 Nov 2010
  • views: 1854
videos
Learn how to directly insert data coming from an Excel file or a text file in Interactive Analysis. This data can either enrich an existing document or be analyzed to find new information.
https://wn.com/Create_A_Query_Based_On_An_Excel_Or_Text_File
Create a query based on an Excel file: SAP BusinessObjects Web Intelligence 4.0

Create a query based on an Excel file: SAP BusinessObjects Web Intelligence 4.0

  • Order:
  • Duration: 0:59
  • Updated: 06 Jan 2015
  • views: 7435
videos
In this video, we will create a new Web Intelligence document based on a local Microsoft Excel spreadsheet. Visit us at http://www.sap.com/LearnBI to view our full catalog of interactive SAP BusinessObjects BI Suite tutorials.
https://wn.com/Create_A_Query_Based_On_An_Excel_File_Sap_Businessobjects_Web_Intelligence_4.0
Making Sense of Temporal Queries with Interactive Visualization

Making Sense of Temporal Queries with Interactive Visualization

  • Order:
  • Duration: 2:06
  • Updated: 06 Jun 2016
  • views: 65
videos
To help analysts better understand temporal queries, we developed StreamTrace, an interactive visualization tool that breaks down how a temporal query processes a given dataset, step-by-step. We demonstrate that StreamTrace can help users to verify that queries behave as expected and to isolate the regions of a query that may be causing unexpected results. http://research.microsoft.com/
https://wn.com/Making_Sense_Of_Temporal_Queries_With_Interactive_Visualization
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