Business Intelligence made easy! This is the first part of a two-part presentation I prepared for one of our customers to help them understand what Business Intelligence is and what can it do...
This presentation will help you understand the basic building blocks of Business Intelligence. Learn how decisions are triggered, the complete decision process and who makes decisions in the corporate world.
More importantly, understand core components of a Business Intelligence architecture such as a data warehouse, data mining, OLAP (Online analytical procession) , OLTP (Online Transaction Processing) and data reporting. Each component plays an integral part which enables today's managers and decision makers collect, analyze and interpret data to make it actionable for decision making.
Business intelligence has become an integral part that needs to be incorporated to ensure business survival. It is a tool that helps analyze historical data and forecast future so that your are always one step ahead in your business.
Please feel free to like, share and comment as you please!
Download at http://DavidHubbard.net/powerpoint - This Introduction to Business Intelligence gives an overview of how Business Intelligence fits into business strategy in general. It does not go into the specific technologies of Business Intelligence. It is meant to be used to explain Business Intelligence to those not already familiar with Business Intelligence.
Business Intelligence made easy! This is the first part of a two-part presentation I prepared for one of our customers to help them understand what Business Intelligence is and what can it do...
This presentation will help you understand the basic building blocks of Business Intelligence. Learn how decisions are triggered, the complete decision process and who makes decisions in the corporate world.
More importantly, understand core components of a Business Intelligence architecture such as a data warehouse, data mining, OLAP (Online analytical procession) , OLTP (Online Transaction Processing) and data reporting. Each component plays an integral part which enables today's managers and decision makers collect, analyze and interpret data to make it actionable for decision making.
Business intelligence has become an integral part that needs to be incorporated to ensure business survival. It is a tool that helps analyze historical data and forecast future so that your are always one step ahead in your business.
Please feel free to like, share and comment as you please!
Download at http://DavidHubbard.net/powerpoint - This Introduction to Business Intelligence gives an overview of how Business Intelligence fits into business strategy in general. It does not go into the specific technologies of Business Intelligence. It is meant to be used to explain Business Intelligence to those not already familiar with Business Intelligence.
The Institution's Innovation Council (Ministry of HRD initiative) and the Institution of Electronics and Telecommunication Engineers (IETE) invited me to grace "World Telecommunication & Information Society Day" on 18 May 2020.
What is business intelligence and where it is applicable is described in this presentation. The subject is offered as elective to BE IT students of Pune University.
Business intelligence- Components, Tools, Need and Applicationsraj
As part of the research project for the course Technical Foundations of Information Systems at the University of Illinois, our team worked on the topic, Business Intelligence. The presentation focuses on what is Business Intelligence, its various components, latest tools, the need of BI as well as applications of this technology. This project deals with the latest development of BI technologies (hardware or software) and includes comprehensive literature survey from Journals, and the Internet.
Business Intelligence And Business Analytics | ManagementTransweb Global Inc
Business Intelligence is the initial basic step of Business Analytics. It refers to gathering raw and complex data, and converting it into systematic and logical information in a format that is usable by the end user. Copy the link given below and paste it in new browser window to get more information on Business Intelligence And Business Analytics:-
http://www.transtutors.com/homework-help/management/managing-information-technology/business-intelligence-analytics/
how to successfully implement a data analytics solution.pdfbasilmph
The adoption of data analytics in business has demonstrated a transformative power in modern entrepreneurship. By analyzing vast reservoirs of data, businesses can make informed decisions, optimize operations and predict trends, thus fueling growth.
The Institution's Innovation Council (Ministry of HRD initiative) and the Institution of Electronics and Telecommunication Engineers (IETE) invited me to grace "World Telecommunication & Information Society Day" on 18 May 2020.
What is business intelligence and where it is applicable is described in this presentation. The subject is offered as elective to BE IT students of Pune University.
Business intelligence- Components, Tools, Need and Applicationsraj
As part of the research project for the course Technical Foundations of Information Systems at the University of Illinois, our team worked on the topic, Business Intelligence. The presentation focuses on what is Business Intelligence, its various components, latest tools, the need of BI as well as applications of this technology. This project deals with the latest development of BI technologies (hardware or software) and includes comprehensive literature survey from Journals, and the Internet.
Business Intelligence And Business Analytics | ManagementTransweb Global Inc
Business Intelligence is the initial basic step of Business Analytics. It refers to gathering raw and complex data, and converting it into systematic and logical information in a format that is usable by the end user. Copy the link given below and paste it in new browser window to get more information on Business Intelligence And Business Analytics:-
http://www.transtutors.com/homework-help/management/managing-information-technology/business-intelligence-analytics/
how to successfully implement a data analytics solution.pdfbasilmph
The adoption of data analytics in business has demonstrated a transformative power in modern entrepreneurship. By analyzing vast reservoirs of data, businesses can make informed decisions, optimize operations and predict trends, thus fueling growth.
Driving Business Performance with Microsoft Performance ManagementNic Smith
Learn how Microsoft technology supports your initative for performance management. PerformancePoint Server completes an end-to-end vision for Microsoft BI and enables organizations to monitor, analyze, and plan to drive results.
No matter how fast business moves, there’s no substitute for a smart, carefully crafted IT plan that is aligned with your business strategy. At SQLSaturday Baton Rouge, Sparkhound Principal Consultant Tim Goedeke discussed his experiences as a fractional CIO, challenged with helping IT fulfill its role as a strategic business partner for speed to market, product / service differentiation and superior end-user experience delivery. Are you ready to eliminate perceptions of IT as a cost center, and paint the vision of IT as a business driver?
Data analytics tools help organizations derive insights from vast amounts of data, enabling informed decision-making, identifying trends and patterns, personalizing customer experiences, optimizing processes, and driving innovation and competitive advantage.
Pluto7 - Tableau Webinar on enabling Organization to be Data Driven in 201...Manju Devadas
Big Data and BI initiatives needs a holistic strategy and execution. The content walks through how an organization became data driven in less than 6 months with Tableau, Alteryx, Splunk and traditional BI enabled by Pluto7 ( www.pluto7.com )
This presentation gives the introduction about cloud storage & its limitations, Introduction to world's first underwater data center which is Microsoft's Underwater Cloud Storage project called "Natick" with its deployment.
Application of Geographical concepts and Spatial Technology to the “Internet ...AkashBorse2
This presentation gives the introduction about concept of Smart City, Internet of Things (IoT), Spatial Computing Technologies and its models along with some case studies.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Show drafts
volume_up
Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
2. •“A technology-driven process for analyzing data and
presenting actionable information to help executives,
managers and other corporate end users make informed
business decisions”
•It is an Umbrella term that combines Architecture,Tools,
Databases, Analytical Model, Applications and
Methodologies.
3.
4. •Accelerating and Improving Decision-Making
•Optimizing internal business processes
•Increasing operational efficiency
•Driving new revenues and gaining competitive advantage
over business rivals
•Identify market trends and spot business problems that
need to be addressed
5.
6. •Analytics – program that builds quantitative processes for a
business to arrive at optimal decisions and to perform
business knowledge discovery.
•Reporting/enterprise reporting – program that builds
infrastructure for strategic reporting to serve the strategic
management of a business, not operational reporting.
7. •Collaboration/collaboration platform – program that
gets different areas (both inside and outside the business)
to work together through data sharing and electronic data
interchange.
•Knowledge management – program to make the
company data-driven through strategies and practices to
identify, create, represent, distribute, and enable adoption
of insights and experiences that are true business
knowledge.
8. •It is an information system that supports business or
organizational decision-making activities.
•It helps people to make decisions about problems that may
be rapidly changing and not easily specified in advance
9. 1. The Database (or Knowledge base)
2. The Model (i.e.The Decision context and User Criteria)
3. The User Interface
10. •Yellowfin BI
•Clear Analytics
•SAP BI
•Oracle hyperion system
•Oracle business intelligence enterprise
edition(OBIEE)
•Pentaho BI
•Business Intelligence and ReportingTools (BIRT)
•Sisence
•JasperSoft
