• "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
  • 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
  • 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
  • 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
  • Interactive Data Analytics and Visualization with Collaborative Documents

    Hassan Chafi, Director, Research & Advanced Development, Oracle Zeppelin, Jupyter, Databricks: notebooks are everywhere. This session presents the Oracle Labs Data Studio, a JVM-based notebook interface for data analysts built on Apache Zeppelin and Oracle JavaScript Extension Toolkit (Oracle JET). It shows use cases that focus on graph visualization and how to visually apply graph algorithms with interpreters such as Apache Spark, databases, and the graph analytic framework PGX. Using notebooks, you can combine different languages such as Groovy, Scala, Python, and the new property graph query language PGQL together with powerful JavaScript-based visualization techniques. The interactive graph visualization supports highlighting, expansion, filter application, and much more. Everything i...

    published: 04 Oct 2017
  • Web Query Excel 2016: Importing data from a website to your spreadsheet

    Recorded with http://screencast-o-matic.com

    published: 15 Nov 2016
  • Building Interactive Data Applications at Scale

    published: 05 Jun 2015
  • 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
  • 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
  • Create an Interactive Form with Power Query

    Do you want to add some interactivity to your Excel? You send the Excel file to someone and they can input some cell and have some output dynamically change. Plus do this without writing any VBA! You can do this with Power Query. Though it does involves editing some of the M code (the language Power Query uses), it's not tooooo much. This can also be known as a parameter query because you are passing (some) user defined parameter to the query for it to do some work. This involves creating two queries in Power Query - (1) a function query and then (2) a plain query from a form (basically a table) where someone enters information. See the video to check out the steps. P.S. Feel free to provide a comment or share it with a friend! ----------------------------------------------------...

    published: 20 Sep 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
  • 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 Exploration with SciDB

    A Shinyapp visualization using 1000 Genomes data.

    published: 16 Mar 2015
  • Grouping Data with Power Query

    Grouping data is a common thing most analyst do. If you use Pivot Tables you are most likely grouping data. You can also group data with the Power Query feature in the Excel Power BI tools, but why would you want to do that if you already have the powerful options in a Pivot Table? Well there are some sophisticated things you can do with grouping in Power Query like further manipulating data within the grouped records. It involves learning M code, the query language used in Power Query. I'm not a guru in M language but I was able to understand some of the basics to do this. If I can learn this, so can you! P.S. Feel free to provide a comment or share it with a friend! ------------------------------------------------------------------------------------------------- Subscribe to th...

    published: 04 Dec 2016
  • 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
  • Dynamics 365: Power BI Query Accelerator

    Microsoft Power BI combines a collection of software services, apps, and connectors to turn your complex sources of data into a visual and interactive format. However, when connecting to Dynamics CRM, there is still a lot of data cleaning needed before it is in a user-friendly state to begin creating Dashboard components. Power BI Query Accelerator was designed by Sonoma Partners to get your Power BI environment set up in a fraction of the time! To download: http://www.sonomapartners.com/tools/powerbiqueryaccelerator

    published: 07 Jun 2017
  • Apache Carbondata: An Indexed Columnar File Format for Interactive Query by Jacky Li/Jihong Ma

    Realtime analytics over large datasets has become an increasing wide-spread demand, over the past several years, Hadoop ecosystem has been continuously evolving, even complex queries over large datasets can be realized in an interactive fashion with distributed processing framework like Apache Spark, new paradigm of efficient storage were introduced as well to facilitate data processing framework, such as Apache Parquet, ORC provide fast scan over columnar data format, and Apache Hbase offers fast ingest and millisecond scale random access. In this talk, we will outline Apache Carbondata, a new addition to open source Hadoop ecosystem which is an indexed columnar file format aimed for bridging the gap to fully enable real-time analytics abilities. It has been deeply integrated with Spark ...

    published: 14 Feb 2017
  • SQL for Beginners. Learn basics of SQL in 1 Hour

    SQL is a special-purpose programming language designed for managing data in a relational database, and is used by a huge number of apps and organizations. Watch this Video to learn basics of SQL. This Video covers below topics about SQL. 0:01 What is SQL? 2:07 Creating a Table and Inserting Data 5:52 Querying The Table 8:03 Aggregating Data 11:24 Queries with AND OR 15:59 Querying IN subqueries 21:22 Restricting Grouped Results with HAVING 25:52 Calculating results with CASE 31:51 JOINing tables 37:15 Joining related tables with left outer joins 41:21 Changing Rows with UPDATE and DELETE 45:54 ALTERing tables after creation 49:51 Joining tables to themselves with self joins 53:50 Combining multiple joins By watching this Video we can learn how to use #SQL to store, query,...

    published: 11 Jul 2015
  • Use SlamData to Query Both 2- and Multi-Dimensional Data and Build Charts Fast

    Learn how to use SQL² to query both two dimensional and multidimensional data, use JOINs across multiple data sources and generate beautiful charts. New to SlamData or Visual Analytics for NoSQL? Watch this short introductory video to get immediate value from SlamData. 100% open source software that runs 100% natively inside your NoSQL database! No ETL, no relocation. Use a powerful form of SQL (SQL²) on top of MongoDB, Elastic, and more!

    published: 11 Jan 2016
  • TPL Hackathon 2015 - Interactive Query System

    published: 27 Nov 2015
  • Building Petabyte scale Interactive Data warehouse in Azure HDInsight - BRK3355

    Come learn to understand real world challenges associated with building a complex, large-scale data warehouse in the cloud. Learn how technologies such as Low Latency Analytical Processing [LLAP] and Hive 2.x are making it better by dramatically improved performance and simplified architecture that suites the public clouds. In this session, we go deep into LLAP’s performance and architecture benefits and how it compares with Spark and Presto. We also look at how business analysts can use familiar tools such as Microsoft Excel and Power BI, and do interactive query over their data lake without moving data outside the data lake.

    published: 28 Sep 2017
  • Excel Web Data Query

    Use the Excel Web Query to grab data from a web page and bring it into Excel

    published: 25 Aug 2010
  • Interactive Exploratory Analytics with Druid | DataEngConf SF '17

    Recorded at DataEngConf '17: 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, ...

    published: 22 Jul 2017
  • Real Time API Data pulled into Excel using Microsoft BI tools Power Pivot, Power Query, & Power View

    This video gives an overview of the process by which to pull Seattle Real Time Fire 911 Calls data into Excel using an API. The API is called using Microsoft Power Query, the data is then modeled in Power Pivot, and an interactive data visualization is shown using Microsoft Power View. The API data can be refreshed throughout the day to obtain updated data from the source database.

    published: 29 Jul 2014
  • Interactively Query and Search your big data

    published: 30 Jun 2015
  • WSO2 Fraud Detection Solution

    The WSO2 Fraud Detection Solution uses batch, real-time, predictive, and interactive analytics capabilities of WSO2 Data Analytics Server to convert domain knowledge into generic rules, implement fraud scoring, utilize Markov models and data clustering to model unknown types of fraud, and obtain interactive data querying and visualizations.

    published: 29 Oct 2015
  • ভিডিওতে দেখুন রোহিঙ্গা মুসলিমদের বর্বর নির্যাতনের চিত্র !!!

    ভিডিওতে দেখুন রোহিঙ্গা মুসলিমদের বর্বর নির্যাতনের চিত্র !!! ----------------------------------------------------------------- Fair Use Disclaimer: This channel may use some copyrighted materials without specific authorization of the owner but contents used here falls under the “Fair Use” as described in The Copyright Act 2000 Law No. 28 of the year 2000 of Bangladesh under Chapter 6, Section 36 and Chapter 13 Section 72. According to that law allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. ------------------------------------------------------------...

    published: 29 Aug 2017
  • Apache Hive Installation Step by step in Ubuntu

    http://www.hadooptpoint.com/ Apache Hive Installation Step by step in Ubuntu ,hive installation on hadoop cluster,hive installation on windows,install hadoop-hive ubuntu Hive is a batch processing system and hive jobs takes much latency to execute the quires comparing to other databases like Oracle.In Oracle databases it can supports only GBs of data but in Hive we can execute More than TBs of data.Hive aims to provide acceptable (but not optimal) latency for interactive data browsing, queries over small data sets or test queries.

    published: 10 May 2016
  • SQL for Beginners. Learn basics of SQL in 1 Hour

    SQL is a special-purpose programming language designed for managing data in a relational database, and is used by a huge number of apps and organizations. Watch this Video to learn basics of SQL. This Video covers below topics about SQL. 0:01 What is SQL? 2:07 Creating a Table and Inserting Data 5:52 Querying The Table 8:03 Aggregating Data 11:24 Queries with AND OR 15:59 Querying IN subqueries 21:22 Restricting Grouped Results with HAVING 25:52 Calculating results with CASE 31:51 JOINing tables 37:15 Joining related tables with left outer joins 41:21 Changing Rows with UPDATE and DELETE 45:54 ALTERing tables after creation 49:51 Joining tables to themselves with self joins 53:50 Combining multiple joins By watching this Video we can learn how to use #SQL to store, query,...

    published: 11 Jul 2015
developed with YouTube
"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: 7097
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
RINSE: Interactive Data Series Exploration

RINSE: Interactive Data Series Exploration

  • Order:
  • Duration: 2:42
  • Updated: 11 Jun 2015
  • views: 648
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
Interactive Data Visualization with Power View

Interactive Data Visualization with Power View

  • Order:
  • Duration: 1:15:53
  • Updated: 20 May 2014
  • views: 64655
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
Interactive Data Analysis

Interactive Data Analysis

  • Order:
  • Duration: 28:06
  • Updated: 20 Nov 2013
  • views: 213
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
Interactive Data Analytics and Visualization with Collaborative Documents

Interactive Data Analytics and Visualization with Collaborative Documents

  • Order:
  • Duration: 44:56
  • Updated: 04 Oct 2017
  • views: 51
videos
Hassan Chafi, Director, Research & Advanced Development, Oracle Zeppelin, Jupyter, Databricks: notebooks are everywhere. This session presents the Oracle Labs Data Studio, a JVM-based notebook interface for data analysts built on Apache Zeppelin and Oracle JavaScript Extension Toolkit (Oracle JET). It shows use cases that focus on graph visualization and how to visually apply graph algorithms with interpreters such as Apache Spark, databases, and the graph analytic framework PGX. Using notebooks, you can combine different languages such as Groovy, Scala, Python, and the new property graph query language PGQL together with powerful JavaScript-based visualization techniques. The interactive graph visualization supports highlighting, expansion, filter application, and much more. Everything is preconfigured and executable directly from the browser.
https://wn.com/Interactive_Data_Analytics_And_Visualization_With_Collaborative_Documents
Web Query Excel 2016: Importing data from a website to your spreadsheet

Web Query Excel 2016: Importing data from a website to your spreadsheet

  • Order:
  • Duration: 6:40
  • Updated: 15 Nov 2016
  • views: 20675
videos
Recorded with http://screencast-o-matic.com
https://wn.com/Web_Query_Excel_2016_Importing_Data_From_A_Website_To_Your_Spreadsheet
Building Interactive Data Applications at Scale

Building Interactive Data Applications at Scale

  • Order:
  • Duration: 42:57
  • Updated: 05 Jun 2015
  • views: 1135
videos
https://wn.com/Building_Interactive_Data_Applications_At_Scale
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: 1671
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
Visualization and Interactive Data Analysis - DataEDGE 2013

Visualization and Interactive Data Analysis - DataEDGE 2013

  • Order:
  • Duration: 53:53
  • Updated: 15 Jun 2013
  • views: 2496
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
Create an Interactive Form with Power Query

Create an Interactive Form with Power Query

  • Order:
  • Duration: 9:36
  • Updated: 20 Sep 2017
  • views: 1086
videos
Do you want to add some interactivity to your Excel? You send the Excel file to someone and they can input some cell and have some output dynamically change. Plus do this without writing any VBA! You can do this with Power Query. Though it does involves editing some of the M code (the language Power Query uses), it's not tooooo much. This can also be known as a parameter query because you are passing (some) user defined parameter to the query for it to do some work. This involves creating two queries in Power Query - (1) a function query and then (2) a plain query from a form (basically a table) where someone enters information. See the video to check out the steps. P.S. Feel free to provide a comment or share it with a friend! ------------------------------------------------------------------------------------------------- Subscribe to the Blog: http://myexcelcharts.blogspot.com
https://wn.com/Create_An_Interactive_Form_With_Power_Query
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: 11391
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
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: 6653
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 Exploration with SciDB

Interactive Data Exploration with SciDB

  • Order:
  • Duration: 8:44
  • Updated: 16 Mar 2015
  • views: 929
videos
A Shinyapp visualization using 1000 Genomes data.
https://wn.com/Interactive_Data_Exploration_With_Scidb
Grouping Data with Power Query

Grouping Data with Power Query

  • Order:
  • Duration: 18:24
  • Updated: 04 Dec 2016
  • views: 14167
videos
Grouping data is a common thing most analyst do. If you use Pivot Tables you are most likely grouping data. You can also group data with the Power Query feature in the Excel Power BI tools, but why would you want to do that if you already have the powerful options in a Pivot Table? Well there are some sophisticated things you can do with grouping in Power Query like further manipulating data within the grouped records. It involves learning M code, the query language used in Power Query. I'm not a guru in M language but I was able to understand some of the basics to do this. If I can learn this, so can you! P.S. Feel free to provide a comment or share it with a friend! ------------------------------------------------------------------------------------------------- Subscribe to the Blog: http://myexcelcharts.blogspot.com
https://wn.com/Grouping_Data_With_Power_Query
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: 6246
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
Dynamics 365: Power BI Query Accelerator

Dynamics 365: Power BI Query Accelerator

  • Order:
  • Duration: 1:29
  • Updated: 07 Jun 2017
  • views: 574
videos
Microsoft Power BI combines a collection of software services, apps, and connectors to turn your complex sources of data into a visual and interactive format. However, when connecting to Dynamics CRM, there is still a lot of data cleaning needed before it is in a user-friendly state to begin creating Dashboard components. Power BI Query Accelerator was designed by Sonoma Partners to get your Power BI environment set up in a fraction of the time! To download: http://www.sonomapartners.com/tools/powerbiqueryaccelerator
https://wn.com/Dynamics_365_Power_Bi_Query_Accelerator
Apache Carbondata: An Indexed Columnar File Format for Interactive Query by Jacky Li/Jihong Ma

Apache Carbondata: An Indexed Columnar File Format for Interactive Query by Jacky Li/Jihong Ma

  • Order:
  • Duration: 30:13
  • Updated: 14 Feb 2017
  • views: 997
videos
Realtime analytics over large datasets has become an increasing wide-spread demand, over the past several years, Hadoop ecosystem has been continuously evolving, even complex queries over large datasets can be realized in an interactive fashion with distributed processing framework like Apache Spark, new paradigm of efficient storage were introduced as well to facilitate data processing framework, such as Apache Parquet, ORC provide fast scan over columnar data format, and Apache Hbase offers fast ingest and millisecond scale random access. In this talk, we will outline Apache Carbondata, a new addition to open source Hadoop ecosystem which is an indexed columnar file format aimed for bridging the gap to fully enable real-time analytics abilities. It has been deeply integrated with Spark SQL and enables dramatic acceleration of query processing by leveraging efficient encoding/compression and effective predicate push down through Carbondata’s multi-level index technique.
https://wn.com/Apache_Carbondata_An_Indexed_Columnar_File_Format_For_Interactive_Query_By_Jacky_Li_Jihong_Ma
SQL for Beginners. Learn basics  of SQL in 1 Hour

SQL for Beginners. Learn basics of SQL in 1 Hour

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  • Duration: 57:13
  • Updated: 11 Jul 2015
  • views: 1051989
videos
SQL is a special-purpose programming language designed for managing data in a relational database, and is used by a huge number of apps and organizations. Watch this Video to learn basics of SQL. This Video covers below topics about SQL. 0:01 What is SQL? 2:07 Creating a Table and Inserting Data 5:52 Querying The Table 8:03 Aggregating Data 11:24 Queries with AND OR 15:59 Querying IN subqueries 21:22 Restricting Grouped Results with HAVING 25:52 Calculating results with CASE 31:51 JOINing tables 37:15 Joining related tables with left outer joins 41:21 Changing Rows with UPDATE and DELETE 45:54 ALTERing tables after creation 49:51 Joining tables to themselves with self joins 53:50 Combining multiple joins By watching this Video we can learn how to use #SQL to store, query, and manipulate data. And, you can watch the original interactive talk-through on Khan Academy, where you can pause and edit the code and see the code in better resolution at https://www.khanacademy.org/computing/computer-programming/sql or learn SQL from http://www.w3schools.com/sql/sql_intro.asp I created this video with the YouTube Video Editor (http://www.youtube.com/editor) with creative commons permission videos provided by Khan Academy Computer Science Subscribe to our YouTube channel at http://www.youtube.com/subscription_center?add_user=qualitypointtech Buy T-Shirts and other Merchandise at https://shop.spreadshirt.com/QualityPointTech/
https://wn.com/Sql_For_Beginners._Learn_Basics_Of_Sql_In_1_Hour
Use SlamData to Query Both 2- and Multi-Dimensional Data and Build Charts Fast

Use SlamData to Query Both 2- and Multi-Dimensional Data and Build Charts Fast

  • Order:
  • Duration: 12:00
  • Updated: 11 Jan 2016
  • views: 2266
videos
Learn how to use SQL² to query both two dimensional and multidimensional data, use JOINs across multiple data sources and generate beautiful charts. New to SlamData or Visual Analytics for NoSQL? Watch this short introductory video to get immediate value from SlamData. 100% open source software that runs 100% natively inside your NoSQL database! No ETL, no relocation. Use a powerful form of SQL (SQL²) on top of MongoDB, Elastic, and more!
https://wn.com/Use_Slamdata_To_Query_Both_2_And_Multi_Dimensional_Data_And_Build_Charts_Fast
TPL Hackathon 2015 - Interactive Query System

TPL Hackathon 2015 - Interactive Query System

  • Order:
  • Duration: 5:15
  • Updated: 27 Nov 2015
  • views: 94
videos
https://wn.com/Tpl_Hackathon_2015_Interactive_Query_System
Building Petabyte scale Interactive Data warehouse in Azure HDInsight - BRK3355

Building Petabyte scale Interactive Data warehouse in Azure HDInsight - BRK3355

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  • Duration: 1:09:47
  • Updated: 28 Sep 2017
  • views: 203
videos
Come learn to understand real world challenges associated with building a complex, large-scale data warehouse in the cloud. Learn how technologies such as Low Latency Analytical Processing [LLAP] and Hive 2.x are making it better by dramatically improved performance and simplified architecture that suites the public clouds. In this session, we go deep into LLAP’s performance and architecture benefits and how it compares with Spark and Presto. We also look at how business analysts can use familiar tools such as Microsoft Excel and Power BI, and do interactive query over their data lake without moving data outside the data lake.
https://wn.com/Building_Petabyte_Scale_Interactive_Data_Warehouse_In_Azure_Hdinsight_Brk3355
Excel Web Data Query

Excel Web Data Query

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  • Duration: 4:46
  • Updated: 25 Aug 2010
  • views: 4026
videos
Use the Excel Web Query to grab data from a web page and bring it into Excel
https://wn.com/Excel_Web_Data_Query
Interactive Exploratory Analytics with Druid | DataEngConf SF '17

Interactive Exploratory Analytics with Druid | DataEngConf SF '17

  • Order:
  • Duration: 36:33
  • Updated: 22 Jul 2017
  • views: 443
videos
Recorded at DataEngConf '17: 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 enterprises are switching to Druid for analytics, and we will cover why the technology is a good fit for its intended use cases. Speaker: Fangjin Yang, Imply
https://wn.com/Interactive_Exploratory_Analytics_With_Druid_|_Dataengconf_Sf_'17
Real Time API Data pulled into Excel using Microsoft BI tools Power Pivot, Power Query, & Power View

Real Time API Data pulled into Excel using Microsoft BI tools Power Pivot, Power Query, & Power View

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  • Duration: 6:49
  • Updated: 29 Jul 2014
  • views: 16299
videos
This video gives an overview of the process by which to pull Seattle Real Time Fire 911 Calls data into Excel using an API. The API is called using Microsoft Power Query, the data is then modeled in Power Pivot, and an interactive data visualization is shown using Microsoft Power View. The API data can be refreshed throughout the day to obtain updated data from the source database.
https://wn.com/Real_Time_Api_Data_Pulled_Into_Excel_Using_Microsoft_Bi_Tools_Power_Pivot,_Power_Query,_Power_View
Interactively Query and Search your big data

Interactively Query and Search your big data

  • Order:
  • Duration: 35:37
  • Updated: 30 Jun 2015
  • views: 104
videos
https://wn.com/Interactively_Query_And_Search_Your_Big_Data
WSO2 Fraud Detection Solution

WSO2 Fraud Detection Solution

  • Order:
  • Duration: 6:14
  • Updated: 29 Oct 2015
  • views: 1177
videos
The WSO2 Fraud Detection Solution uses batch, real-time, predictive, and interactive analytics capabilities of WSO2 Data Analytics Server to convert domain knowledge into generic rules, implement fraud scoring, utilize Markov models and data clustering to model unknown types of fraud, and obtain interactive data querying and visualizations.
https://wn.com/Wso2_Fraud_Detection_Solution
ভিডিওতে দেখুন রোহিঙ্গা মুসলিমদের বর্বর নির্যাতনের চিত্র !!!

ভিডিওতে দেখুন রোহিঙ্গা মুসলিমদের বর্বর নির্যাতনের চিত্র !!!

  • Order:
  • Duration: 1:59
  • Updated: 29 Aug 2017
  • views: 1117342
videos
ভিডিওতে দেখুন রোহিঙ্গা মুসলিমদের বর্বর নির্যাতনের চিত্র !!! ----------------------------------------------------------------- Fair Use Disclaimer: This channel may use some copyrighted materials without specific authorization of the owner but contents used here falls under the “Fair Use” as described in The Copyright Act 2000 Law No. 28 of the year 2000 of Bangladesh under Chapter 6, Section 36 and Chapter 13 Section 72. According to that law allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. ----------------------------------------------------------------- ----------------------------------------------------------------- When you like our video then thumps up the like button and share your valuable comment bellow the comment box. And share the video your facebook for great audience retention. Don't forget the subscribe the channel Bangla Viral News. Thank you so much and thanks a lot again. ----------------------------------------------------------------- ----------------------------------------------------------------- You get the channel bangla viral news all bd news available here. we collect all news form be news paper. bangldesh news paper is so usefull for us. Such a day bangla news paper today is greatfull for us. We collect news form all bangladeshi newspaper. Rather that a bd news paper today. We also collect from online bangladeshi newspaper. online bangla newspaper is useful for us. We also collect news from daily all bangla news paper. This the so easy for us that free bangla newspaper online is also grateful. We are thanks to all bangladesh newspapers. ----------------------------------------------------------------- ----------------------------------------------------------------- Please like the video. share your comment bellow the video, and Obviously Share our video. Please don't forget the Subscribe our Channel. ----------------------------------------------------------------- ----------------------------------------------------------------- You get the channel bangla viral news all bd news available here. we collect all news form be news paper. bangldesh news paper is so usefull for us. We are so proud fill for you. Such a day bangla news paper today is greatfull for us. We collect news form all bangladeshi newspaper. Rather that a bd news paper today. Thanks you so much for your activeness. We also collect from online bangladeshi newspaper. online bangla newspaper is useful for us. We also collect news from daily all bangla news paper. This the so easy for us that free bangla newspaper online is also grateful. We are thanks to all bangladesh newspapers. Bangla Viral News beside every time and everywhere with you. ----------------------------------------------------------------- ----------------------------------------------------------------- bangla viral news makes reasonable efforts to implement technology and security features in order to safeguard the privacy of its users from loss, unauthorized access or improper use. bangla viral news may store your information in its databases, such as a Customer Relationship database, for reference. The information may be retained and used by bangla viral news for a reasonable period, reflecting our need to answer queries or resolve problems, provide improved and new services and any data retention requirements of the law. This means we may retain information after an individual has ceased interacting with us. bangla viral news does not sell, rent or give your personal data to any third party except where the law permits or unless you specifically agree. Users of the site are invited to inform bangla viral news services on any dysfunctions of the site in the light of privacy rights. In its capacity as a news agency, bangla viral news gathers and stores what could be classified as personal data. This is used for news reporting, opinion polls and related research. This privacy notice does not focus on that type of use. Like most websites bvnnews.blogspot.com also collects information through the use of technology. Among other things, a cookie may identify your browser and store information such as the date and time you access the site and the pages visited. ----------------------------------------------------------------- ----------------------------------------------------------------- Again Thanks for subscribe our channel.
https://wn.com/ভিডিওতে_দেখুন_রোহিঙ্গা_মুসলিমদের_বর্বর_নির্যাতনের_চিত্র
Apache Hive Installation Step by step in Ubuntu

Apache Hive Installation Step by step in Ubuntu

  • Order:
  • Duration: 44:41
  • Updated: 10 May 2016
  • views: 1200
videos
http://www.hadooptpoint.com/ Apache Hive Installation Step by step in Ubuntu ,hive installation on hadoop cluster,hive installation on windows,install hadoop-hive ubuntu Hive is a batch processing system and hive jobs takes much latency to execute the quires comparing to other databases like Oracle.In Oracle databases it can supports only GBs of data but in Hive we can execute More than TBs of data.Hive aims to provide acceptable (but not optimal) latency for interactive data browsing, queries over small data sets or test queries.
https://wn.com/Apache_Hive_Installation_Step_By_Step_In_Ubuntu
SQL for Beginners. Learn basics  of SQL in 1 Hour

SQL for Beginners. Learn basics of SQL in 1 Hour

  • Order:
  • Duration: 57:13
  • Updated: 11 Jul 2015
  • views: 866899
videos
SQL is a special-purpose programming language designed for managing data in a relational database, and is used by a huge number of apps and organizations. Watch this Video to learn basics of SQL. This Video covers below topics about SQL. 0:01 What is SQL? 2:07 Creating a Table and Inserting Data 5:52 Querying The Table 8:03 Aggregating Data 11:24 Queries with AND OR 15:59 Querying IN subqueries 21:22 Restricting Grouped Results with HAVING 25:52 Calculating results with CASE 31:51 JOINing tables 37:15 Joining related tables with left outer joins 41:21 Changing Rows with UPDATE and DELETE 45:54 ALTERing tables after creation 49:51 Joining tables to themselves with self joins 53:50 Combining multiple joins By watching this Video we can learn how to use #SQL to store, query, and manipulate data. And, you can watch the original interactive talk-through on Khan Academy, where you can pause and edit the code and see the code in better resolution at https://www.khanacademy.org/computing/computer-programming/sql or learn SQL from http://www.w3schools.com/sql/sql_intro.asp I created this video with the YouTube Video Editor (http://www.youtube.com/editor) with creative commons permission videos provided by Khan Academy Computer Science Subscribe to our YouTube channel at http://www.youtube.com/subscription_center?add_user=qualitypointtech Buy T-Shirts and other Merchandise at https://shop.spreadshirt.com/QualityPointTech/
https://wn.com/Sql_For_Beginners._Learn_Basics_Of_Sql_In_1_Hour