DOCSLIB.ORG

Business Intelligence with Sharepoint and Project Server

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Business Intelligence with Sharepoint and Project Server Sundar Rajan, PMP Agenda: Case study – dashboards the old way Interactive Look Ahead Report Using Power BI Visualizations Power BI with Project Online Power BI with Project Server A look at Power BI applications elsewhere Scheduling options Q&A Even measuring your sleep quality! Business intelligence, or BI, is an umbrella term that refers to a variety of software applications used to analyze an organization's raw data BI as a discipline is made up of several related activities, including data mining, online analytical processing, querying and reporting Self-service business intelligence is an approach to data analytics that enables business users to access and work with corporate data even though they do not have a background in statistical analysis, business intelligence (BI) or data mining. Feb 3, 2016 The article below takes you step by step on getting MS Project data into an Access database Creating Access database from MS Project schedule Log into PowerBI service Navigate to datasets ACMS Assignment usage - > Click Report Drop a slicer for Work Stream Customize to horizontal and frame items Drop a table, select Task fields Drop a slicer for Finish (Date visualization) See how selecting Workstream or Finish drives Task data display PowerBI Content Pack for Project Online Creating-burndown-charts-for-project Extending the PowerBI content pack for Project Online Step by Step MPUG article on GANTT custom visual Using the Power BI GANTT Visualzation for your Projects Desktop MS Project Project Online Project Server Task Updates Spreadsheets and email PWA – Individual PWA – Individual (cumbersome) updates updates Reporting and Limited Visual Reports REST API – SQL SSRS (Full SQL Server Dashboards Export to Excel reports Reporting) Data Visualizations Export to Access Power BI Power BI (Cumbersome) OLAP (Pivot tables) N/A N/A Excel Pivots Cube Data generated Nightly Cost $600 per user $54 premier, $8 Expensive users per month Implementation Single day Easy for Private 6-9 Month Orgs A project by itself State - needs liaison with CDT Establish Schedule standards for Analysis Outline levels Custom columns e.g. Work Stream IPOR – Schedule Analysis Create a Content Pack of Schedule QA and Analysis dashboards Run these against schedules PSR Create a Content Pack of Schedule Analysis dashboards • Presentation Layer • BI Designer • Advanced Power BI Report creation • Power User • Department focused Power BI Report creation • Consumer • End user that consumes Power BI Reports and Dashboards • Semantic Layer • Data Modeler • Organize, clean and contribute to transform data into business semantics. • BI Architect • Task with understanding the business, the data and the questions – oversee and maps “Any data, anywhere, any • Data Layer • DBA time” • Creates and Assist with Company’s enterprise data. • IT Administration • Task with sever administration, including Power BI Enterprise Gateway. - Bryant Avey, Chief Geek, internuntius The only thing that gives an organization a “competitive edge...is what it knows, how it uses what it knows and how fast it can know something. ” - Larry Prusak (1996) 5 seconds to sign up. 5 minutes to wow! Power BI delivers custom data visualization to business teams • Bringing the power of data visualization to business users • “Power BI and custom visualizations fuel our self- service BI culture” 23 | 2/13/2017 | Self Service BI Model Free PowerBI Desktop Mobile enabled Monthly Enhancements by community user requests (voting) Natural language queries (‘R’ language) • Alexa like (Cortana) ntegration New Content packs all the time • SharePoint • Microsoft CRM • GitHUB • Twitter • Facebook • Project Online • Project Server (SQL Server and OLAP) Update cycle – user requests! Magic Quadrant for Business Intelligence and Analytics Platforms ! Power BI is *NOT* business intelligence. Business Intelligence is an on-going strategy You can not buy business intelligence. You can buy tools and technology but BI is about people and data. Power BI is a set of tools and technologies. PAST: What Happened? • Reactive reporting • Common among most companies PRESENT: What is Happening? • KPI’s and CPM Concepts • Streaming analytics FUTURE: What will Happen? • Predict based on trends and external data • Understand impact and what-if analysis Microsoft Power BI • Cloud based service (Part of Office 365) • Access to all data, wherver it may live • Ask questions, integrate with cortana analytics and more • Create curated content based on your company needs • Share insights across web, mobile and embedded within your own applications. “Any data, anywhere, any time” Twitter Analytics Facebook Analytics Sales and Marketing Sample (with natural language queries) Project Online Content Pack SharePoint Lists and Document Libraries Extending Project Online Content Pack Sales Scorecard Live Dashboard SQL Server Info Power BI Dashboard Portfolio Slicer for Power BI - investment tracking Create your personalized Twitter Analytics Dashboard in Power BI in 10 minutes! Sales and Marketing Sample (with natural language queries) SQL Server Info Dashboard • Free download that starts your Power BI experience. • Not an end user tool, but a power user and designer tool. • Can be used to mash, model and design engaging experiences. • Transform and clean data • Design once and view anywhere “Any data, anywhere, any time” Visualizations Measures (Expressions) Data Modelling Diverse Data Sources (CRM, SharePoint, GitHUB, SQL Server) • Consume from almost any device • Microsoft • Android • Apple – Including Apple Watch • Set alerts that allow for proactive engagement • Offline cache for dashboard consumption without an internet connection. “Any data, anywhere, any time” Dashboard on phone Look at early response to Power BI (Microsoft) SQL Server Info Power BI Dashboard Power BI and SharePoint – Step by step on how to use Power BI with SP Power BI Guiding Learning: https://powerbi.microsoft.com/en-us/guided- learning/ PowerBI.com Blog: https://powerbi.microsoft.com/en-us/blog/.
Load more

Recommended publications
  • Dashboard Design for Real-Time Situation Awareness
    Dashboard Design for Real-Time Situation Awareness Stephen Few, author of Information Dashboard Design Dashboard Design for Real-Time Situation Awareness Few if any recent trends in business information delivery have inspired as much enthusiasm as dashboards. When they work, they provide a powerful means to tame the beast of data overload. Despite their popularity, however, most dashboards live up to only a fraction of their potential. They fail, not because of poor technology—at least not primarily—but because of poor design. The more critical that information is to the well being of the business, the more grievous is the failure, because the remedy is so readily available. The term “dashboard” refers to a single screen information display that is used to monitor what’s going on in some aspect of the business. The key word is “monitor.” A dashboard presents the key data that you must effi ciently monitor to maintain awareness of what’s going on in your area of responsibility. Most dashboards are used to monitor information once a day, because more frequent use is unnecessary given the rate at which the information changes and speed at which responses must be made. Some jobs, however, require constant monitoring in real time, or close to it, because the activities that you track are happening right now and delays in responding can’t be tolerated. There is perhaps no better example of this type of dashboard than one that monitors the brisk and sometimes harried activities of a call center. Much like air traffi c control systems or cockpits in airplanes, call center dashboards must be designed to support real-time “situation awareness.” They must grab your attention when it’s needed, they must make it easy to spot what’s most important in a screen full of data, and they must give you the means to understand what’s happening and respond without delay.
    [Show full text]
  • Business Intelligence: a Discussion on Platforms, Technologies, and Solutions
    Business Intelligence: A Discussion on Platforms, Technologies, and solutions Tutorial RCIS 2013-Paris May 29-31 Introduction • Presenters: – Noushin Ashrafi • [email protected] – Jean-Pierre Kuilboer • [email protected] • Time and Discussion Frame – 90 minutes • Audiene can ask questions any time during presentation. 4/19/2013 RCIS 2013-Paris May 29-31 2 Tutorial overview knowledge Discovery from Data • The Thrust of the tutorial is to examine Business Intelligence (BI) Platforms to develop business analytics applications. • Specifically, we will address: – Requirements, development , and capabilities of the BI. – Self-service, enterprise, and cloud BI. – Confusing BI concepts such as: Platform, infrastructure, technology and architecture . – Solutions by three well-known vendors: Microsoft, TableauSoftware and IBM. 4/19/2013 RCIS 2013-Paris May 29-31 3 Overview of Business Intelligence • BI is revolutionizing decision making and information technology across all industries. This phenomenon is largely due to the ever-increasing availability of data. • The explosive volumes of data are available in both structured and unstructured formats, and are analyzed and processed to become information within context hence providing relevance, and purpose to the decision making process. 4/19/2013 RCIS 2013-Paris May 29-31 4 4/19/2013 RCIS 2013-Paris May 29-31 5 What is Business Intelligence? • BI is a content-free expression, so it means different things to different people. • BI is neither a product, nor a service – BI refers to people, processes, technologies and practices used to support business decision making. 4/19/2013 RCIS 2013-Paris May 29-31 6 4/19/2013 RCIS 2013-Paris May 29-31 7 What is Business Intelligence? • BI is an umbrella term that combines architectures, technology, analytical tools, applications, and methodologies to help transform data, to information, to knowledge, to decisions, and finally to action.
    [Show full text]
  • IBM Infosphere Master Data Management
    Data and AI Solution Brief IBM InfoSphere Master Data Management Maintain a trusted, accurate view of Highlights critical business data in a hybrid environment • Support comprehensive, cost-effective information Organizations today have more data about products, governance services, customers and transactions than ever before. • Monitor master data quality Hidden in this data are vital insights that can drive business using dashboards and results. But without comprehensive, well-governed data proactive alerts sources, decision-makers cannot be sure that the information • Simplify the management they are using is the latest, most accurate version. As data and enforcement of master volumes continue to grow, the problem is compounded over data policies time. Businesses need to find new ways to manage and • Integrate master data govern the increasing variety and volume of data and deliver management into existing it to end users as quickly as possible and in a trusted manner, business processes regardless of the computing modality. • Quickly scale to meet changing business needs IBM InfoSphere Master Data Management (InfoSphere MDM) provides a single, trusted view of critical business data to • Optimize resources using users and applications, helping to reduce costs, minimize risk flexible deployment options and improve decision-making speed and precision. InfoSphere MDM achieves the single view through highly accurate and comprehensive matching that helps overcome differences and errors that often occur in the data sources. The MDM server manages your master data entities centrally, reducing reliance on incomplete or duplicate data while consolidating information from across the enterprise. Data and AI Solution Brief With InfoSphere MDM, you can enforce information governance at an organizational level, enabling business and IT teams to collaborate on such topics as data quality and policy management.
    [Show full text]
  • Montana COVID-19 Cases Map and Dashboard Metadata
    Montana COVID-19 Cases Map and Dashboard Metadata For assistance, please e-mail or call the Montana Joint Information Center 1-888-333-0461 A list of FAQs and answers related to COVID-19 can be found here. Updates to the information are made by 11:30 a.m. daily. Description: The data for this dashboard is derived from local health officials at the county level who report cases to the Montana Department of Health and Human Services (DPHHS). DPHHS tabulates case data and then gives the data to the Montana State Library to publish through this web feature service. The daily updates are managed by the Disaster & Emergency Service State Emergency Coordination Center. Montana public health agencies and the Governor's Coronavirus Task Force are actively working to limit the spread of novel coronavirus in Montana. The Montana State Library is assisting the effort by geo-enabling public health information to help decision-makers, State Emergency Coordination Center and the Governor's Coronavirus Task Force, understand the spread of the disease. Information is reported based on the previous day. Information on the dashboard and maps will change based on further public health investigation. Cumulative Cases Indicator: This includes all reported Montana residents meeting the CDC case definition for novel coronavirus infections, and some non-Montana residents who were diagnosed with novel coronavirus infections while in Montana. New Cases Indicator: Daily aggregate of new cases in Montana, reported to DPHHS, for the previous full day. These newly reported cases can be classified as either active or recovered. Updates to the information are run by 11:30 a.m.
    [Show full text]
  • Governance by Dashboard
    Governance by Dashboard A Policy Paper Jamie Bartlett Nathaniel Tkacz Open Access. Some rights reserved. As the publisher of this work, Demos wants to encourage the circulation of our work as widely as possible while retaining the copyright. We therefore have an open access policy which enables anyone to access our content online without charge. Anyone can download, save, perform or distribute this work in any format, including translation, without written permission. This is subject to the terms of the Demos licence found at the back of this publication. Its main conditions are: · Demos and the author(s) are credited · This summary and the address www.demos.co.uk are displayed · The text is not altered and is used in full · The work is not resold · A copy of the work or link to its use online is sent to Demos. You are welcome to ask for permission to use this work for purposes other than those covered by the licence. Demos gratefully acknowledges the work of Creative Commons in inspiring our approach to copyright. To find out more go to www.creativecommons.org PARTNERS CREDITS This report was commissioned by: Published by Demos March 2017 © Demos. Some rights reserved. Unit 1, 2-3 Mill Street London SE1 2BD T: 020 7367 4200 [email protected] www.demos.co.uk CONTENTS Foreword 5 Introduction 7 The rise of the data dashboard 9 Dashboards in action 11 Dashboards transformation 14 Factors for successful dashboard implementation 18 4 5 FOREWORD Data dashboards – interfaces which display complex data to a user, often displayed in real time, and typically drawn from multiple sources – are an increasingly important way in which government departments make decisions.
    [Show full text]
  • Business Intelligence Dashboard for Academic Program Management
    Paper ID #13300 Business Intelligence Dashboard for Academic Program Management Dr. Mudasser Fraz Wyne, National University I have a Ph.D. in Computer Science, M.Sc. in Engineering, and B.Sc. in Electrical Engineering. Currently I serve as a Chair for Department of Computer Science, Information and Media Systems and Professor of Computer Science at School of Engineering and Computing, National University. I am also the Program Lead for MS in Information Technology Management and have also served recently as the lead for BSc in Information Systems, the co-Lead for MSc Computer Science and Program Lead for MSc in Database Administration programs. My association with ABET (Accreditation Board of Engineering and Technol- ogy) US dates back to 2001, as a certified program evaluator for BSc in Computer Science and BSc in Information Systems. At present, I am also serving as the Commissioner for the Computer Accredita- tion Commission (CAC). Previously, I have taught at 6 different countries for over 25 years. I have been privileged to be part of the DESY Group (Deutches Elecktronen Synchrotron), Hamburg Germany, as a research fellow, and worked with an MIT group, led by a Nobel laureate. On the research side, I have been fortunate enough to secure a number of grants and have served on numerous international Ph.D. Thesis committees, been a member of the editorial boards for 7 interna- tional journals, and served as the Chair and Co-Chair for 12 international conferences. For recognition of my research activities, I have been invited to a number of international conferences as Invited Speaker, chaired panel discussions and numerous international conference sessions.
    [Show full text]
  • Business Intelligence: Dashboard
    International Journal of Engineering Research & Technology (IJERT) ICONECT' 14 Conference Proceedings Business Intelligence: Dashboard Tushar Mulik1, Pravin Malusare2, Omkar Takalkar3,Prof. Monali Patil4 Department of Information Technology Mumbai University Mumbai, India [email protected],2 [email protected], 3 [email protected], 4 [email protected] Abstract - Business intelligence systems combine operational intelligence is viewed as being proactive. Essential data with analytical tools to present complex and competitive components of proactive BI are: information to planners and decision makers. The objective is • Real-time data warehousing, to improve the timeliness and quality of inputs to the decision • Data mining, process. Business Intelligence is used to understand the • Automated anomaly and exception detection, capabilities available in the firm; the state of the art, trends, and future directions in the markets, the technologies, and the •Proactive alerting with automatic recipient regulatory environment in which the firm competes; and the determination, actions of competitors and the implications of these actions. • Seamless follow-through workflow, The emergence of the data warehouse as a repository, advances • Automatic learning and refinement, in data cleansing, increased capabilities of hardware and • Geographic information systems software, and the emergence of the web architecture all • Data visualization combine to create a richer business intelligence environment than was available previously. II. LITERATURE SURVEY Much has been said and written about BI systems. To begin I. INTRODUCTION the research, study begins with collecting information from Demand for Business Intelligence (BI) applications periodicals, journals and reports. BI systems are used almost continues to grow even at a time when demand for most in all the sectors of industry for different purposes like information technology (IT) products is soft.
    [Show full text]
  • Design Concepts for an Outage Control Center Information Dashboard
    INL/EXT-15-37425 Rev. 0 De sign Concepts for an Outage Control Center Information Dashboard Jacques Hugo Shawn St. Germain Ronald Farris Cheradan Thompson McKenzie Whitesides December 2015 The INL is a U.S. Department of Energy National Laboratory operated by Battelle Energy Alliance DISCLAIMER This information was prepared as an account of work sponsored by an agency of the U.S. Government. Neither the U.S. Government nor any agency thereof, nor any of their employees, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness, of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. References herein to any specific commercial product, process, or service by trade name, trade mark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the U.S. Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the U.S. Government or any agency thereof. INL/EXT-15-37425 Rev. 0 Design Concepts for an Outage Control Center Information Dashboard Jacques Hugo Shawn St. Germain Ronald Farris Cheradan Thompson McKenzie Whitesides December 2015 Idaho National Laboratory Idaho Falls, Idaho 83415 http://www.inl.gov Prepared under Work Package L-12N060305 Prepared for the U.S. Department of Energy Office of Nuclear Energy Under DOE Idaho Operations Office Contract DE-AC07-05ID14517 EXECUTIVE SUMMARY The nuclear industry, and the business world in general, is facing a rapidly increasing amount of data to be dealt with on a daily basis.
    [Show full text]
  • Prototype and Deployment of a Big Data Analytics Platform
    Prototype and Deployment of a Big Data Analytics Platform CTT2.0 Carbon Track and Trace Deliverable D3.1 Atle Vesterkjær, Patrick Merlot (Numascale) Oslo, Norway| 14 December 2016 climate-kic.org Contents Preface ................................................................................................................................................................. 2 Requirement Analysis ........................................................................................................................................ 3 Previous E2E Analytics IoT platform ....................................................................................................................... 3 CTT Analytics IoT platform ......................................................................................................................................... 5 State of the art technology overview ..................................................................................................................... 6 Adaption of standard and develop-ment of custom components ............................................................. 7 Standard components ................................................................................................................................................. 7 Custom components .................................................................................................................................................... 9 Deployment of the platform ............................................................................................................................
    [Show full text]
  • Study on Business Intelligence Tools for Enterprise Dashboard Development
    International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 04 | Apr -2017 www.irjet.net p-ISSN: 2395-0072 Study on Business Intelligence Tools for Enterprise Dashboard Development K.Gowthami1, M.R. Pavan Kumar2 1Student(M.Tech), Dept of CSE, Sree Vidyanikethan Engineering College, Tirupati, India. 2Assistant Professor, Dept. Of CSE, Sree Vidyanikethan Engineering College, Tirupati, India. ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - This paper presents detailed information on dashboards, OLAP and data mining to charting and ETL. It Business Intelligence (BI) tools for developing a dashboard covers all the analytic areas of Business Intelligence in a typical enterprise setup. Few most popular BI tools like projects, with innovative themes and engines. The SpagoBI SpagoBI, Power BI, Tableau, Qliksense and Jaspersoft are server includes an interactive dashboard and integration with other reporting tools. considered based on the ease of use, support in terms of training and minimal initial cost at the end, a sample SpagoBI mainly consists of the following modules: dashboard has been developed using one of the tools Power BI to demonstrate the feasibility of the same for the Business data visualization. Key Words: Dashboard, Business Intelligence, Data Reports, Visualization, Data Analytics. 1.INTRODUCTION Business Analytic or Business Intelligence (BI) is becoming more needed by the top management of any enterprise to visualize, analyze and prepare the strategic Fig 1: SpagoBI Architecture planning for the future. However, the availability of business intelligence tools, the support on the existing SpagoBI Server, It includes analytic tools and features infrastructure (including software and hardware), act as a core for the suite.
    [Show full text]
  • Fast Database Restarts at Facebook
    Fast Database Restarts at Facebook ∗ Aakash Goel, Bhuwan Chopra, Ciprian Gerea, Dhrúv Mátáni, Josh Metzler, Fahim Ul Haq, and Janet L. Wiener Facebook, Inc. ABSTRACT 1. INTRODUCTION Facebook engineers query multiple databases to monitor and Facebook engineers query multiple database systems to analyze Facebook products and services. The fastest of monitor and analyze Facebook products and services. Scuba[5] these databases is Scuba, which achieves subsecond query is a very fast, distributed, in-memory database used exten- response time by storing all of its data in memory across sively for interactive, ad hoc, analysis queries. These queries hundreds of servers. We are continually improving the code typically run in under a second over GBs of data. Scuba pro- for Scuba and would like to push new software releases at cesses almost a million queries per day for over 1500 Face- least once a week. However, restarting a Scuba machine book employees. In addition, Scuba is the workhorse behind clears its memory. Recovering all of its data from disk | Facebook's code regression analysis, bug report monitoring, about 120 GB per machine | takes 2.5-3 hours to read and ads revenue monitoring, and performance debugging. format the data per machine. Even 10 minutes is a long One significant source of downtime is software upgrades, downtime for the critical applications that rely on Scuba, yet upgrades are necessary to introduce new features and such as detecting user-facing errors. Restarting only 2% of apply bug fixes. At Facebook, we are accustomed to the the servers at a time mitigates the amount of unavailable agility that comes with frequent code deployments.
    [Show full text]
  • Designing Dashboards for Multiple Target Audiences with SAS Visual
    Paper SAS4323-2020 Designing Dashboards for Multiple Target Audiences with SAS® Visual Analytics Kunal Shah, SAS Institute Inc. ABSTRACT There is no doubt that organizations have a vast amount of data available at their disposal. Yet, they often fall into the trap of creating a single dashboard for a wide variety of audiences to derive meaningful insights from the available data. Different audiences expect different insights from the data. Even the dashboard design thinking differs based on the target audience. This presentation focuses on three key audiences (executives, middle management, and individual contributors) and how to use SAS® Visual Analytics to create dashboards that generate powerful insights for each of these. The presentation also covers dashboard design best practices and recommendations from field consultants to help you weave a compelling story from your organizational data. INTRODUCTION Dashboards have become a popular tool in today’s business world. They are designed and implemented by nearly every industry, non-governmental organization (NGO), and even educational institution to enable data-driven decision making. There are literally hundreds of solutions that incorporate some kind of dashboard building capability. Yet, very little attention has been paid to the design and usability of these dashboards. Deriving value out of data isn’t just about defining a laundry list of success metrics but rather communicating a story and compelling the user to take action. Traditionally, dashboards are designed with data in mind - the amount of data, the kind of data, and the type of graph/chart to visualize the data. Users end up cramming a bunch of charts and gauges into a single dashboard and would eventually find themselves trying to fit in a large amount of organizational data into limited screen space.
    [Show full text]