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Some like R, others like Python, or have been using other statistical or data mining environments. Tableau works with its many partners to allow you to leverage your investment and knowledge in other platforms, and use Tableau to compose beautiful data stories. This session will cover how Tableau's different analytics partners integrate with Tableau, and how you can take advantage of synergies between them to take your analysis to the next level.
This session is also available at the following time(s): Wednesday at 10:45 am and Thursday at 9:00 am
Forecasting in Tableau is a simple as drag and drop, but how does Tableau's forecasting really work—behind the drag and drop? Why does forecasting behave the way it does? How can you change Tableau's forecasting model? Why doesn’t your forecast work? How can you leverage R? In this session, we will explore Tableau's forecasting capabilities as well as forecasting capabilities with R. Get ready to predict the future!
Dell HR leverages Tableau and Tableau Server to perform routine reporting, advanced reporting, advanced analytics, and predictive modeling on a dynamic 150 thousand team member workforce. Learn how the techniques used to show reconciliation reporting, org. hygiene, turnover, shoring, and costs, can be replicated quickly and easily at your enterprise.
Learn how to apply several advanced HR analytics techniques using a simple data set and Tableau. We’ll demonstrate how to construct a time to proficiency visualization that explains how all previous and future new hires can reach key levels of proficiency from their hire date(s). Using built in functions of fits, filtering and colors understand the relationship between your HR on-boarding and the effects on performance.
Want to integrate R into your workflow, both before and during your analysis in Tableau Desktop? Come to this hands-on training to get familiar with the R environment, learn how to manipulate data directly in R, and finally bring that data into Tableau. Once in Tableau, we’ll show you how to use the R-Integration feature to make calls directly to R to open up the rich statistical features of R to Tableau. In this session you’ll learn:
- How data goes back and forth
- How to debug common issues in R-Integration
- How to optimize the performance of the calls
This session is also available at the following time(s): Wednesday at 10:45 am
Visa offers dozens of products to financial institutions, merchants, and consumers that are powered by applications that run on "virtual machine" servers in Visa data centers. Managing the underlying hardware requires the ability to forecast future server needs well in advance, to ensure that equipment is in place when it is needed. Forecasting anything involving technology using only historical-based trends is fraught with peril, so a forecasting model that allows for user adjustments is important. This session will detail out a technical approach for building an interactive Tableau forecasting model that combines historical-based forecasting with user-controlled adjustments.
The approach involves:
- Creating "placeholder" data for the forecast
- Lots of table calculations to apply the forecasting logic
- Using parameters to make adjustments to the forecast
The BAE Systems Workforce Intelligence team within HR was tasked with creating dashboard to inform on the health of their workforce, conduct a flight risk analysis, create workflows for compliance, and much more. We faced dirty data in Excel, dashboards that were coded in SQL, and running predictive analytics using R code and a Microsoft Access database. But in 2015, Josh Kabler, Lead BI Technologist, attended TC15 and saw how Alteryx could make the team more scalable by dealing with the disparate data sources and through workflows that did not require any SQL or R coding. Attend this session to learn how an HR team tackled their data preparation and enabled advanced analytics and is now revolutionizing analytics throughout BAE Systems.
In 2014 PATH and the Tableau Foundation launched #VisualizeNoMalaria, an initiative to support the Zambian Ministry of Health to eliminate malaria by 2020. This session will showcase the community efforts of PATH, the volunteers including several Tableau Zen Masters, and the Tableau, Alteryx, and Mapbox communities to develop dashboards, alerts, and predictive models to support the work in Zambia. We will present a technical overview of the Tableau dashboards built to support the data pipeline, geospatial and predictive analytics using Alteryx, Mapbox, and Tableau, and VizAlerts for distributing dashboards to a variety of staff in Zambia. Come to this session to learn about this critical use case and be inspired about how you can do good with data.
This session is also available at the following time(s): Tuesday at 10:45 am and Thursday at 9:00 am
This session is also available at the following time(s): Tuesday at 10:45 am
Here's your chance to see a Tableau engine developed in GM's Advanced Analytics to power adaptation of data visualization and find new roads to data insight. This case study will show some practical examples on how to tune your own workbook engine to provide decision drivers with a winning dashboard. The OEM optional equipment package demonstrated in this data vehicle will show how to lay down some skid marks with the pages shelf and smoke Excel and PowerPoint off the starting line.
R-Integration is a powerful feature of Tableau. It combines the extensibility and statistical power of R with the drag-and-drop ease-of-use of Tableau. In this session, we will explore the possibilities of R-Integration in both Tableau Desktop and Server, and learn some advanced strategies for bringing the power of R into Tableau. If you have never used R-Integration before, come see why people are excited about the feature and the possibilities it opens up to Tableau. If you are already familiar with R, come learn more about how it works behind the scenes, and how to make your workbooks faster and easier to use.
This session is also available at the following time(s): Thursday at 12:00 pm
This session is also available at the following time(s): Tuesday at 10:45 am and Wednesday at 10:45 am
In this presentation, you will learn the process of building a parameter-driven "What If" tool that allows users to dynamically explore a statistical model created in Python. We'll focus on the modeling process, extract generation using the TDE API, dashboard design, and the derivation of business insights. We will also share alternative approaches and discuss challenges we faced during development.
Today's changing risk environment has set us on a path where the proper use of data analytics and data visualization are becoming critical to any high performing organization. Increasing volumes of data, multiple enterprise data sets, numerous controls and more complex fraud schemes all require the greater use of technology in order to properly analyze all the enterprise data in an effective and efficient manner. Traditional risk identification techniques have worked well in the past but changes must be made to allow an organization's risk team to keep up with the increasing complexity of their organization's electronic footprint.
Data analytics and data visualization are quickly becoming critical components within many risk functions of an organization. The Board, Internal audit, the Controller's office and the C-Suite are all looking for data-driven decisions that are based off of the continuous monitoring and continuous auditing of enterprise data. An organization's risk staff can use mathematical optimization of audit schedules, automatic notification of high-risk data elements and predictive and prescriptive analytics to enhance their ability to reduce corporate risk and drive operational improvement back into the business. These techniques help an organization see, prepare for and adapt to changes within their business environment.
During this sessions, you will see how Tableau can help your organization;
- Perform more audits with less resources
- Identify which entities should be audited and how the audit should be scheduled
- Quickly identify and risk-rank high-risk elements within your organization
- Effectively use all available electronic data and eliminate statistical sampling
- Develop more data-driven actionable insights to reduce overall corporate risk
- Utilize statistical functions such as correlation coefficients and liner regressions to help identify a vendor or employee that may, in the future, perform a high risk act.
Organizations that utilize data analytics and data visualization within their risk functions are able to much more effectively gain insight into business process controls and quickly identify high-risk transactions, vendors or employees from within an increasingly complex data environment. When done right, analytics will allow the risk group to better understand the risk profile of their organization, be able to make better data driven decisions when it comes to risk and provide answers to the Board and the Executive team about not only what is happening within the organization now from a risk perspective but what might happen in the future.
This session is also available at the following time(s): Wednesday at 3:15 pm
Note: Content is still being added to the schedule. Sessions, times, and locations are subject to change.