AI + Machine Learning , Azure Machine Learning , Internet of Things , Thought leadership

Solve your toughest business problems with analytics and machine learning
By Sonal Pardeshi Director, Data & AI
Posted on August 17, 2021 3 min read
Today, AI and machine learning are enabling data-driven organizations to accelerate their journey to insights and decisions. With all the latest advancements, AI is no longer limited to only those with deep expertise or a cache of data scientists, and many organizations can now adopt AI and machine learning for better competitive advantage. Customers with analytics practices looking to adopt machine learning can read this report, Aboard The Analytics Train? Machine Learning's Your Next Stop , to get started. The report contains a maturity model as well as customer examples to help accelerate your journey with AI.
Machine learning has many applications across a broad set of industries and scenarios. Using machine learning in addition to traditional analytics, organizations can, for example, predict their sales forecast, identify their next new revenue growth opportunity, gain insights on their most profitable products, and more, resulting in a far greater return on investment (ROI).
Bring AI and machine learning to everyone
Azure Machine Learning is an enterprise-grade machine learning service to build and deploy models with machine learning operations (MLOps) capabilities to streamline the machine learning lifecycle and help automate it. It provides deep integration with Azure Synapse Analytics, a limitless analytics service that brings together data integration, enterprise data warehousing, and big data analytics. Azure Machine Learning and Azure Synapse Analytics together help enable stronger collaboration between data engineers and data scientists, so they can build models with ease, enrich the enterprise’s data, and create even greater outcomes with their data.
Customers vested in analytics typically already have streamlined data processes, workflows, and teams in place and while there are synergies to be had from adding machine learning to the mix, there are also areas where additional investment will be required. AGL is one such Azure customer and a leader in Australia’s energy sector. AGL set up combined analytics and Machine Learning Center of Excellence (CoE) to create significant scalable and sustainable value through data and analytics for use cases that span optimizing procurement for power plants, forecasting demand, improving customer experiences, and more. They used Azure Synapse Analytics and Azure Databricks for data engineering and analytics, and Azure Machine Learning for quick and cost-effective training, deployment, and lifecycle management for thousands of parallel models. The architecture incorporates on-demand at-scale training, end-to-end model, and code management, automated MLOps deployments, model hosting, and performance monitoring.
“With Azure Machine Learning, we’re increasing speed-to-value while reducing cost-to-value.”— Sarah Dods, Head of Advanced Analytics, AGL
Another Azure customer, BRF, one of the largest food companies in the world, had a strong analytics practice and had already experimented with a successful machine learning use case. They built on this over time and established a CoE for advanced analytics and machine learning. Using Azure Synapse Analytics and Azure Machine Learning with its built-in MLOps capabilities, they solved many more use cases such as forecasting disease among livestock, customer purchase recommendations, traffic risks, and more.
“We already had a strong analytics practice and with the help of Azure Machine Learning we were able to better align to new use cases and quickly develop innovative product recommendation solutions for our customers.”— Wellington Monteiro, Global Data Science Chapter Lead, BRF
The company expects the continued alignment of its analytics and machine learning practices to generate commercial and operating advantages as it moves through the maturity levels of the combined analytics and machine learning lifecycle.
With seamless integrations and advanced capabilities, Azure Machine Learning and Azure Synapse Analytics make it easier for organizations to build a machine learning practice to achieve their business objectives. And organizations can accelerate their success by augmenting analytics with machine learning through a multi-stage maturity approach.
- To learn more, read the report by Blue Badge Insights .
- Get started with Azure Machine Learning today—use the free trial .
Let us know what you think of Azure and what you would like to see in the future.
Provide feedback
Build your cloud computing and Azure skills with free courses by Microsoft Learn.
Explore Azure learning
Related posts
AI + Machine Learning , Announcements , Azure AI , Azure Container Apps , Azure DevOps , Azure Kubernetes Service (AKS) , Azure Machine Learning , Azure OpenAI Service , Microsoft Dev Box
Build next-generation, AI-powered applications on Microsoft Azure chevron_right
AI + Machine Learning , Azure Cognitive Search , Azure Cosmos DB , Azure Machine Learning , Azure OpenAI Service , Events , Microsoft Purview , Text Analytics
What’s new in Azure Data & AI: Helping organizations manage the data deluge chevron_right
AI + Machine Learning , Announcements , Azure Machine Learning , Virtual Machines
What’s new in Azure Data & AI: Azure is built for generative AI apps chevron_right
AI + Machine Learning , Announcements , Azure Machine Learning , Azure OpenAI Service
Azure previews powerful and scalable virtual machine series to accelerate generative AI chevron_right
Wij maken gebruik van cookies. Lees meer hierover in onze privacy statement .
Bezoekersstatistieken, websitebezoek en gebruik wordt gemeten en gebruikersgegevens worden anoniem verzameld.
Geen cookies van dit type!
Klikgedrag, bekeken video’s en aangepaste voorkeuren worden verzameld. Bezoekersinformatie en gebruikersgedrag wordt gebruikt voor advertenties.
Gegevens over de bezoeken van de gebruiker worden verzameld zoals welke pagina’s zijn gelezen.

Analytics enable nonprofits to help people and planet

Nowadays Analytics significantly contributes to the success of companies. Our vision is that Analytics has the same potential to contribute to humanitarian and societal challenges. Our dream is to apply analytics and contribute to the Sustainable Development Goals.
Contribute to the Sustainable Development Goals
We believe that analytics can contribute to solving the major challenges facing humanity: climate, hunger, deforestation, the extinction of flora and fauna, you name it. We’ve already seen the tremendous value that analytics can have for commercial organizations and the time is now ripe to harness their power to help solve these problems.

Achieve the SDGs through the application of analytics
This is how much impact our work can have

Curious to increase and broaden your impact?
We don’t want to restrict ourselves to a single SDG, and the problems we’re addressing are global. We’re looking for large NGOs, public institutions and nonprofits with a global focus that are eager to work with us to achieve the SDGs by applying analytics. We welcome companies with expertise in IT, UX/UI, application development, data science and AI, or large corporations that wish to provide support, either by contributing funds, manpower for projects, or technology licenses and capacity. Philanthropic and charitable funds are also welcome, of course, as are volunteers with data science skills, or with project management or marketing skills.

"Join us, if you want to contribute to a Better World with Analytics!"
Proud founders of the ABW Institute

Meet the team

The personal motivation and vision from the team and our founders

What's happening?

On May 24th, 2023 Analytics for a Better World (ABW) will organise its second annual conference at Amsterdam Business School. Read more about this conference.

On June1, 2022, we organised a launching conference to bring together our key partners, researchers and (potential) sponsors. Our aim was to inspire each other, share ABW’s vision and plans and explore opportunities for collaboration.

We're excited to be covered by Change.inc: who visited our conference and wrote an article highlighting our vision, plans and impactful cases.

Our partner 510, in a pro-bono collaboration with ORTEC (founder of Analytics for a Better World), developed a framework to identify what Data & Digital Maturity looks like across multiple levels. This framework has been adopted in the IFRC’s Digital Transformation strategy to offer a vocabulary of Digital Transformation in multiple contexts and provide a basis to track the process.
Something went wrong, please try again later
Thanks for your registration

Graduate Studies Blog


Disciplines Chevron down icon Chevron up icon
- Start single access now
- Request access for companies
Springer Professional
2015 | Book

Practical Business Analytics Using SAS
A hands-on guide.
Authors: Venkat Reddy Konasani, Shailendra Kadre
Publisher: Apress
Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"
About this book
Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios.
The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS basic functions, you will see how each function can be used to get the information you need to improve business performance. Each chapter offers hands-on exercises drawn from real business situations.
The book then provides an overview of statistics, as well as instruction on exploring data, preparing it for analysis, and testing hypotheses. You will learn how to use SAS to perform analytics and model using both basic and advanced techniques like multiple regression, logistic regression, and time series analysis, among other topics. The book concludes with a chapter on analyzing big data. Illustrations from banking and other industries make the principles and methods come to life.
Readers will find just enough theory to understand the practical examples and case studies, which cover all industries. Written for a corporate IT and programming audience that wants to upgrade skills or enter the analytics field, this book includes:
More than 200 examples and exercises, including code and datasets for practice. Relevant examples for all industries.Case studies that show how to use SAS analytics to identify opportunities, solve complicated problems, and chart a course.
Practical Business Analytics Using SAS: A Hands-on Guide gives you the tools you need to gain insight into the data at your fingertips, predict business conditions for better planning, and make excellent decisions. Whether you are in retail, finance, healthcare, manufacturing, government, or any other industry, this book will help your organization increase revenue, drive down costs, improve marketing, and satisfy customers better than ever before.
Table of Contents
Frontmatter, basics of sas programming for analytics, chapter 1. introduction to business analytics and data analysis tools, chapter 2. sas introduction, chapter 3. data handling using sas, chapter 4. important sas functions and procs, using sas for business analytics, chapter 5. introduction to statistical analysis, chapter 6. basic descriptive statistics and reporting in sas, chapter 7. data exploration, validation, and data sanitization, chapter 8. testing of hypothesis, chapter 9. correlation and linear regression, chapter 10. multiple regression analysis, chapter 11. logistic regression, chapter 12. time-series analysis and forecasting, chapter 13. introducing big data analytics, premium partner.
- Business IT + Informatics
- Construction + Real Estate
- Electrical Engineering + Electronics
- Energy + Sustainability
- Insurance + Risk
- Finance + Banking
- Management + Leadership
- Marketing + Sales
- Mechanical Engineering + Materials

Release Summary
defi SOLUTIONS, auto lending’s leading loan origination system (LOS), announced today the company will be expanding its product offering to include a full-service analytics and reporting platform.
- #heritageliveondefi
Tippie College of Business
Full-time master of business analytics.

Hone your data analytics expertise
Businesses are creating and storing more data than ever before— according to IDG (International Data Group), small and medium-size businesses manage 47.81 terabytes alone. In fact, 90% of all data that exists today was created in the last two years.
Companies are swimming in data but lack the talent and expertise to use it to make decisions, reveal insights, and make predictions. Tippie's Master of Science in Business Analytics (MSBA) program is helping to change that. Our three-semester on-campus program in Iowa City puts students at the forefront of a burgeoning industry clamoring for top-notch talent.
Get an Overview
Check out this quick 15-minute video, where we explain why Tippie's MSBA puts you on the leading edge of a high-demand career and answer common questions from prospective students.

“I’ve learned the fundamentals of how data flows in an org—how we get our hands on the right data, how we visualize it and get it in the hands of decision makers.”
Jaden Prottsman, Master of Business Analytics Read Jaden's story
Develop in-demand skills
Gain the skills and techniques to turn raw data into actionable insights. Descriptive and diagnostic analytics are just the beginning. You’ll also develop the ability to become a decision-maker and data scientist adept at using predictive and prescriptive analytics to solve business problems. On top of all that, you'll become well-versed in clearly communicating your data discoveries.
employed within 6 months of graduation
Among 2021-2022 Graduates

“People in the college of business are very genuine and I’ve developed relationships with members of faculty. We have a culture here where professors will make time for you and provide many extra resources.”
Oluwasayo (Sayo) Taiwo, Master of Business Analytics Read Sayo's story
Work with world-class faculty
Whether it's developing algorithms to predict criminal behavior in metro areas or modeling effective logistics in the wake of a catastrophe, our business analytics faculty are on the cutting edge of the discipline. As a graduate student studying business analytics, you'll work closely with some of the leading researchers in the field.
Informs 2021 UPS George D. Smith Prize for Business Analytics

“It was incredible to see how I could apply all the tools that I learned in the program to my internship at PwC. They used SQL, they used visualization—I felt very comfortable, and very prepared.”
Carla Romagosa, Master of Business Analytics Read Carla's story
Become the new star hire
Nothing speaks louder to employers than real-world experience. A full-time summer internship in analytics can lift your resume to the top of the stack. Tap the solid expertise and connections of our Career Management Center in your internship search and in starting your job search.
Average starting salary
Among 2021-2022 grads
Hands-on learning you won’t find just anywhere
As a full-time master’s student, you’ll have unique opportunities to expand your knowledge in the real world.

Work with a real company to solve their business problems using what you’ve learned.

Join a member of Tippie’s award-winning analytics department for a research-based project.

Internships
An analytics internship will help your resume stand out when it comes to looking for full-time roles after graduation.

Business Analytics Case Competition
Each year, we bring together top analytics graduate students to solve a real-world business problem. Think you’ve got what it takes?
A STEM-designated master's program in business analytics
The full-time MS in Business Analytics at Tippie is designated as a STEM (science, technology, engineering, and math) academic program by the Department of Homeland Security. This designation opens doors to STEM-specific scholarships, grants, financial assistance, and employment opportunities for students and graduates.
For international students, STEM designation means additional opportunities to stay and work in the US—up to three years after graduation—under the STEM OPT program.
More details? Yes, please.
Download our Decision Guide for all the information you need to get in and get started.

IMAGES
VIDEO
COMMENTS
Today, AI and machine learning are enabling data-driven organizations to accelerate their journey to insights and decisions. Customers with analytics practices looking to adopt machine learning can read this report to get started
The TWU MBA with emphasis in business analytics prepare you to solve analytical problems from diverse disciplines such as healthcare, marketing, accounting, finance, economics and human resources
It is the fusion of Statistics, Analytics, Machine Learning and Artificial Intelligence (AI) that enables us to find new ways of analysing data and generating additional insights
Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios
Together, business users and IT can quickly deploy secure, dynamic solutions built to auto-scale, so that organisations can focus on solving business problems and pursue new opportunities
Add to that the vast array of external data sources and analytic products, and the problem increases exponentially. defi SOLUTIONS revolutionized the LOS industry by putting power in the hands of the lender
You'll also develop the ability to become a decision-maker and data scientist adept at using predictive and prescriptive analytics to solve business problems. Each year, we bring together top analytics graduate