AI-Powered Business Intelligence: Improving Forecasts and Decision Making with Machine Learning

Business intelligence can be powered by AI to increase efficiency, improve corporate decision-making, and drive growth. This book explores relevant AI use cases for BI, such as forecasting, automated classification, and recommendation systems, and teaches how to leverage AI-as-a-service and AutoML platforms to implement enterprise-grade proof of concepts.

Format: Paperback / softback
Length: 350 pages
Publication date: 24 June 2022
Publisher: O'Reilly Media

Business intelligence (BI) is a powerful tool that can drive corporate growth, increase efficiency, and improve corporate decision-making. By leveraging artificial intelligence (AI), businesses can gain valuable insights from their data and make informed decisions that lead to success.

One of the most relevant AI use cases for BI is improved forecasting. AI algorithms can analyze large amounts of data and predict future trends with a high degree of accuracy. This can help businesses plan for future growth, identify potential risks, and optimize their operations.

Automated classification is another area where AI can be extremely useful. By analyzing text, image, and voice audio files, AI algorithms can classify these data sources into different categories and provide insights that can help businesses make better decisions. For example, a company can use AI to classify customer feedback and identify recurring issues that need to be addressed.

Recommendation services are also a key component of AI-powered BI. By analyzing customer data and behavior, AI algorithms can provide personalized recommendations to customers. This can help businesses increase customer satisfaction, drive sales, and improve customer retention.

Drawing insights from unstructured data sources like text, image, and voice audio files is another area where AI can be extremely valuable. Natural language processing (NLP) services can help businesses analyze large amounts of text data and extract valuable insights. Computer vision services can also be used to extract information from documents and images.

One of the most exciting aspects of AI-powered BI is the ability to build interactive user interfaces for AI-powered dashboards. With the help of machine learning algorithms, businesses can create dashboards that provide real-time insights and allow users to interact with the data in a more intuitive way.

Implementing an end-to-end case study for building an AI-powered customer analytics dashboard is another way that businesses can demonstrate the value of AI-powered BI. By analyzing customer data and behavior, businesses can create a dashboard that provides insights into customer preferences, purchasing patterns, and customer loyalty.

In conclusion, business intelligence is a powerful tool that can drive corporate growth, increase efficiency, and improve corporate decision-making. By leveraging artificial intelligence, businesses can gain valuable insights from their data and make informed decisions that lead to success. With the help of this practical book, you will explore the most relevant AI use cases for BI, including improved forecasting, automated classification, and AI-powered recommendations. You will also learn how to draw insights from unstructured data sources like text, image, and voice audio files. Author Tobias Zwingmann, senior data scientist and cofounder of Germany-based AI startup RAPYD.AI, will help BI, business, and data analysts understand high-impact areas of predictive and prescriptive analytics. You will learn how to leverage popular AI-as-a-service and AutoML platforms to ship enterprise-grade proof of concepts without the help of software engineers or data scientists. Finally, you will learn how AI can generate business impact in BI environments, use AutoML for automated classification and improved forecasting, implement recommendation services to support decision-making, draw insights from text data at scale with NLP services, extract information from documents and images with computer vision services, make voice audio files accessible for reporting with AI transcription services, build interactive user frontends for AI-powered dashboard prototypes, and implement an end-to-end case study for building an AI-powered customer analytics dashboard.

Weight: 668g
Dimension: 177 x 233 x 25 (mm)
ISBN-13: 9781098111472