TC16_Fostering_a_Successful_Tableau_Deployment

Business requirements are critical to any project. Recent studies show that 70% of organisations fail to gather business requirements well. What is worse is that poor requirements can lead a project to over spend its original budget by 95%. Business Intelligence and Performance Management projects are no different. This session will provide a series of tips, techniques and ideas on how you can discover, analyse, understand and document your business requirements for your BI and PM projects. This session will also touch on specific issues, hurdles and obstacle that occur for a typical BI or PM project • The importance of business requirements and a well defined business requirements process • Understanding the difference between a “wish-list” or vision and business requirements • The need and benefits of having a business traceability matrix Start your BI projects on the right foot – understand your requirements

This document provides information about Bound Tech's Tableau online training course. It discusses the course content, features of Tableau, Tableau course content including data sources, fields operations, calculations, charts, dashboards, and Tableau navigations. The course is taught with real-time examples and scenarios to provide job-oriented Tableau training. It aims to teach students fundamental to advanced Tableau concepts to help them pursue careers in roles like Business Analyst, Data Scientist, and Tableau Expert.

This document template defines an outline structure for the clear and unambiguous definition of analytics & reporting outputs (including standard reports, ad hoc queries, Business Intelligence, analytical models etc).

http://spr.ly/SBOUC_VP - The key to a successful analytics program is to have the right strategy in place. An effective approach benefits both IT and the core business alike. A solid, well-communicated business intelligence strategy is more than just a good idea. It’s crucial to maximizing ROI, reaching KPIs, and identifying metrics that actually mean something. Take the next step in your journey to a solid BI strategy. Presenters: Deepa Sankar & Pat Saporito, SAP

Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.

This document provides an overview of big data analytics, strategies, and the WSO2 big data platform. It discusses how the amount of data in the world is growing exponentially due to factors like increased data collection and the internet of things. It then summarizes the WSO2 big data platform for collecting, processing, analyzing and visualizing large datasets. Key components include the complex event processor for query processing and the business activity monitor for dashboards. The document concludes by outlining new developments and features being worked on, such as distributed complex event processing and machine learning integration.

Tableau is business intelligence software that was created in 1992 as VizQL and allows users to visualize data through drag-and-drop interfaces to create dashboards, charts, and maps. It has three main products - Tableau Desktop for personal use, Tableau Server for organizations, and Tableau Online for cloud-based offerings. Tableau can connect to different data sources and perform functions like mapping, filtering, and unlimited undo. It is an alternative to using Excel for data analysis and visualization, with pros like ease of use but potential cons around cost and capabilities. The business intelligence software market that Tableau operates in continues to grow.

Tableau Drive is a methodology for scaling out self-service analytics. Drive is based on best practices from successful enterprise deployments. The methodology relies on iterative, agile methods that are faster and more effective than traditional long-cycle deployment. A cornerstone of the approach is a new model of a partnership between business and IT. The Drive Methodology is available for free. Some organizations will choose to execute Drive themselves; others will look to Tableau Services or Tableau Partners for expert help.

A presentation given recently by IIBA guest speaker, Nancy Williams, Vice President of BI and Data Warehousing at DecisionPath Consulting

The document discusses developing an analytics strategy to drive healthcare transformation. It begins by outlining signs an analytics strategy is needed, such as having dashboards but no improvement. It then discusses components of an effective analytics strategy, including understanding business context, stakeholders, processes and data, tools and techniques, team and training, and technology. The strategy ensures analytics align with goals and avoids just collecting reports. Developing the strategy involves understanding requirements, identifying gaps, and executing the plan. The strategy provides a framework to guide analytics development and ensure optimal use of resources.

2024 Q1 Tableau User Group Leader Quarterly Call Slides

The document summarizes Ancestry.com's journey to self-service analytics using Tableau. It discusses the challenges with their traditional BI tool, how they evaluated Tableau and other options, and how adopting Tableau helped overcome reporting bottlenecks. Key successes with Tableau included a Mother's Day PR campaign that was their most talked about and successful campaign, and allowing their A/B testing team to complete 40 requests for analysis in 3 days using a Tableau dashboard. Their vision for the future includes expanding Tableau usage to additional departments and data sources.

R is a language and environment for statistical computing and graphics. It provides functions for data manipulation, calculation, and graphical displays. Key features of R include its ability to produce publication-quality plots, perform statistical tests, fit models to data, and develop statistical software. R has an extensive library of additional user-contributed packages that extend its capabilities. The document provides information on downloading and using R, reading data into R, customizing plots, and interactive plotting functions.

This exclusive webinar with top industry visionaries will explore the latest innovations in Artificial Intelligence and the incredible potential of LLMs! We'll walk through two compelling case studies that showcase how AI is reimagining industries and revolutionizing the way we interact with technology.

Data is becoming one of the main decision-makers in an organisation. The more data we have the more challenges we face every day. Every decision we make will have long-term implications. In the talk we will go through different approaches to the data pipelines: from a simple in-house built, with comparison to open source solutions based on Apache stack(Apache Kafka, Apache Samza, Spark) and finally hosted auto-scaling solutions based Amazon(S3, Kinesis, Lambda, EMR) or Google(Pub/Sub, Dataflow, BigQuery). The talk covers the main aspects of data collecting processes altogether with further implications for data processing, highlighting appropriate solutions and architectures for the particular use-cases.

The document discusses a webinar on finding the right market intelligence technology for a company. The webinar will be presented by JP Ratajczak from Aurora WDC and will cover topics like the evolution of MI technology, its impact on the intelligence cycle, short and long term benefits of investment, and what to consider when buying an MI technology solution.

This document describes an online donation system project created by students at SRM Institute of Science and Technology. The system was designed to build an intuitive online platform for donations that allows efficient expansion of support, trusted organization options, and social sharing features. It addresses issues with online donations like confusion over which organizations to donate to and whether they are legitimate. The project uses technologies like Android Studio, Google Cloud Platform, and design tools like Figma. It estimated costs of around Rs. 44,000 and proposed testing techniques including decision table testing, state transition testing, and performance testing.

NTEN is a nonprofit organization that aims to help other nonprofits use technology effectively. It offers training programs, conferences, research reports, and online community groups to support the nonprofit sector. NTEN breaks down complex data projects into discrete tasks that can be completed by both long-term and short-term volunteers, allowing them to leverage volunteer expertise from companies to expand their data analysis capacity beyond what their small staff could handle alone.

n this talk, we talk about the challenges at scale in an organization like Lyft. We delve into data discovery as a challenge towards democratizing data within your organization. And, go in detail about the solution to solve the challenge of data discovery.

Penelope Coventry will give a presentation on PowerApps and Microsoft Flow. She will discuss what these tools are, the relationship between Flow and Logic Apps, when to use each tool, administrative controls for PowerApps and Flow, pricing, and how to get started. Her presentation will include demonstrations and provide resources for learning more about PowerApps and Flow.

apidays LIVE Paris 2021 - APIs and the Future of Software December 7, 8 & 9, 2021 APIs are the new skin of your organisation Marc Burgauer, Agile Coach at Registers of Scotland

This document provides an overview and introduction to data mining using R and Rattle. It discusses data mining concepts and applications. It then introduces R as a programming language for statistical analysis and data mining. Rattle is presented as a graphical user interface tool built on R to make data mining more accessible. The document walks through installing and using Rattle to explore, visualize, model and evaluate data. It also discusses resources for learning more about R, Rattle and data mining.

This document proposes using chatbots as user-friendly interfaces to query open data sources published as web APIs. It describes a model-based approach to automatically generate chatbots for specific open data sources. The chatbots allow both direct queries and guided conversations without needing technical skills. An Eclipse plugin has been implemented to support common open data standards and generate chatbots. The approach aims to make open data more accessible and useful to regular citizens. Future work includes supporting advanced queries, combining multiple data sources, and generating chatbots for open data portals.

Key Takeaways from this presentation include: - How data is used to run day to day operations - How data is used to influence product decisions and marketing strategies - Which skills are necessary to become self-serving in data tasks regardless of core responsibilities

The document discusses big data and machine learning solutions on AWS. It covers why organizations use big data, challenges they face, and how AWS solutions like S3 data lakes, Glue, Athena, Redshift, Kinesis, Elasticsearch, SageMaker, and QuickSight can help overcome these challenges. It also discusses how big data drives machine learning and how AWS machine learning services work. Core tenets discussed include building decoupled systems, using the right tool for the job, and leveraging serverless services.

Leading brands such as Pepsi and Macy’s use Celtra’s technology platform for brand advertising. To inform better product design and resolve issues faster, Celtra relies on Databricks to gather insights from large-scale, diverse, and complex raw event data. Learn how Celtra uses Databricks to simplify their Spark deployment, achieve faster project turnaround time, and empower people to make data-driven decisions. In this webinar, you will learn how Databricks helps Celtra to: - Utilize Apache Spark to power their production analytics pipeline. - Build a “Just-in-Time” data warehouse to analyze diverse data sources such as Elastic Load Balancer access logs, raw tracking events, operational data, and reportable metrics. - Go beyond simple counting and group events into sequences (i.e., sessionization) and perform more complex analysis such as funnel analytics.

Today, companies are capturing information about customers at every touchpoint, but the reality is that most companies are working with siloed marketing data because they’re using disparate tools to track online, offline, web, social, mobile, and advertising data. In this presentation, Rod Fontecilla, VP of Application Modernization at Unisys, explains how his team uses Platfora to analyze, interact and understand data to drive customer success at Unisys. Rod will highlight three specific Unisys use cases of Platfora, one of which involved a timely text survey sentiment analysis that produced insights enabling a course correction in favor of improved customer satisfaction.