LSB Data Camp

Are you tired of spending hours on manual data processing tasks? Do you want to learn how to use extract, transform, and load (ETL) techniques more efficiently so you can focus on the analysis and interpretation of financial data? Then join us for our Data Camp session on Alteryx!

Alteryx is a powerful data analytics and process automation software platform that can help you simplify data preparation, speed up insights, and improve collaboration. Using hands-on practices, we’ll will guide you step-by-step in developing the skills and knowledge you need to get started with the software.

By the end of the module, learners will:

• Understand the benefits of Alteryx and how it can help you streamline data analytics processes and improve decision-making.
• Learn how to use Alteryx’s drag and drop tools for data preparation, including cleaning, blending, and transforming data.
• Learn how to create workflows and automate processes in Alteryx to save time and improve productivity.

Register here for our program on March 28, 2023, from 5-8 p.m. in Sankey 308. Assistant Professor Kevin Agnew of the Department of Accounting is presenting the camp.

The search for predictive patterns from network or graph data are at the core of analytical intelligence and actionable insights. While networks can represent the broad spectrum of data, they are often used when links, relationships, or interconnections are critical to the problem at hand. Examples include networks that link products or customers via usage (or preference) profiles, transaction interactions, or co-citations. Network data science has manifested itself in providing expert recommendations, completing missing links in knowledge graphs, discovering of co-occurring diseases, and detecting frauds, just to name a few.

In this talk, a tasting menu or “dim sum” of network data science techniques will be introduced in a hands-on manner to experience their power in making recommendations, discovering the influencers, or designing portfolio investments. It will be assumed students will have access to either the Google Colab or to the installed version of the Anaconda distribution of Python during the presentation.

Register here for our program on March 21, 2023, from 5-8 p.m. in Sankey 308. Dr. Nagiza Samatova of LexisNexis is presenting the camp.

In this data camp, we will take a deep dive into data visualization technologies and techniques. We will begin to learn the art of understanding the audience and how to navigate the business questions being asked, and we will learn how to create a compelling data driven story to a business executive using Power BI.

By the end of this module, learners will:

• Learn to dissect the business question being asked when tasked with creating a data visualization or dashboard
• Take a deep dive into Power BI. Learn how it can be used to answer a real-world business problem
• Learn to keep an open mind when it comes to visualizing data. The best visualizations require the most creativity

Register here for our program on February 14, 2023. Eric Maxon, a senior marketing analyst for Carolina Biological, is presenting the camp.

In this session, we will examine concepts of data visualization and learn how Tableau can help you make sense of your large dataset. You will also learn how to prepare your data for compelling storytelling. Prof. Ajjan will guide you step-by-step to build a story and convey data insights clearly and directly.

By the end of the module, learners will:

• Build a solid foundation with core concepts and techniques for working with data to create visualizations in Tableau
• Develop an understanding of visual best practices
• Learn how to create a digital story to effectively share your information and insights

Instructor: Dr. Haya Ajjan

In this session, we will examine concepts of data analytics with a special focus on web-based data. Specifically, you will build a solid foundation with core concepts in web-based analytics. You will also apply popular industry-standard analytics tools to analyze web-scale data and gain meaningful insights from them. A mixed teaching approach—a combination of short lectures and hands-on practices—will be adopted to guide you step-by-step to build effective web-based analytics systems to support real-world business decisions.

By the end of the module, learners will be able to:

• Understand the key concepts in web-based analytics, including web development basics, definition and categories of web analytics
• Apply practical analytics techniques for working with web-scale data to support decision-making across multiple business domains following the analytics processes (e.g., data collection, preprocessing, analytical modeling, evaluations, deployment, etc.)
• Evaluate the innovative applications of web analytics in modern businesses and organizations and potentially create new business opportunities

Instructor: Dr. Long Xia

In this module, we’ll learn about R, the free, open source, and powerful statistical software. We’ll use the RStudio developer environment, also free to download, and the R language to import, clean, visualize, and summarize our data. Instructions for set-up (Mac or PC) will be provided.

By the end of the module, we will:

• Learn how to install R, R Studio, and navigate our developer environment.
• Use “Tidyverse” packages and syntax to explore our data.
• Discuss the basics of moving from “point and click” statistical analysis to a more reproducible and automated workflow.

Instructor: Dr. Adam Aiken

In this learning module, we will examine concepts of data mining with a special focus on textual data, which has become a major data format in the business world. Specifically, you will build a solid foundation with core concepts in text mining and analytics. You will also apply popular text mining tools to analyze text data from multiple perspectives (e.g., topic modeling, sentiment analysis, text classification, etc.) and gain meaningful insights. This module will guide you step-by-step to build effective text analytics systems to support real-world business decisions.

By the end of the module, learners will be able to:

• Understand the key concepts in text analytics, including various types of text analytics and how each of them would support practical business operations and decision-making;
• Apply different levels of text analytics algorithms, including basic lexicon-based methods, traditional machine learning, and state-of-the-art deep learning;
• Evaluate the innovative applications of text analytics in modern businesses and potentially create new business opportunities.

Instructor: Dr. Long Xia

In this session, you will learn the basics of Robotic Process Automation and how RPA software can be used to automate repeatable tasks that have been traditionally performed by humans. We will examine the characteristics, benefits, types of robots, and processes suited for RPA. Prof. Agnew will guide you through the process of creating a robot, scraping data, looping, reading data and writing to Excel using UiPath.

By the end of the module, learners will:

• Understand the basics of Robotic Process Automation
• Identify processes that can be automated
• Develop and deploy basic robots independently using UiPath RPA Platform

Instructor: Dr. Kevin Agnew

Join us on for an interactive, hands-on-workshop exploring Machine Learning Operational Implementations (MLOps in brief) on Dataiku’s end-to-end platform for everyday AI.

By the end of the module, learners will:

• Easily access and explore data sources
• Prepare training data
• Build machine learning models
• Deploy one to generate predictions on new, unseen records, and
• Manage a model through its lifecycle

Presented by Dataiku team members Chris Butler, partner solutions architect, Molly Jones, solutions engineer and Andrew Williams, solutions engineer.