Exploring Analytics & AI in 2018: A Detailed Primer

It is often said that data is the most valuable asset a business can have; the oil of a digital era. But data itself, while interesting, often leaves out a variety of important details – creating a need for analytics. And how we complete these analytics has evolved – and will continue to do so; particularly with the rapid proliferation of AI tools and technologies.

Some benefits associated with AI and analytics include:

  • Increased productivity via instant access to the right data through better classification processes
  • Improved speed, accuracy, and efficiency throughout analytics and data management practices
  • Facilitating clear compliance with legal and similar requirements
  • Cost saving by finding the best ways to achieve a wide range of tasks

To better understand data, analytics, AI, and how they all go together, we will answer the following questions: Read more

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Synthetic Data: An Introduction & 10 Tools [07/2018 Update]

Synthetic data, as the name suggests, is data that is artificially created rather than being generated by actual events. It is often created with the help of algorithms and is used for a wide range of activities, including as test data for new products and tools, for model validation, and in AI needs.

The questions that this post sets out to answer include:

Why is synthetic data important and what are some use cases for it?

How does synthetic data perform compared to real data?

What are some benefits associated with synthetic data?

What are some basics of synthetic data creation?

What are some challenges associated with synthetic data?

What are some tools related to synthetic data?

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Retail Analytics: A Guide for Growing Businesses [07/18 Update]

Retail analytics is a process that helps to provide crucial data for businesses with regards to inventory, sales, supply chain activities, consumer demand, and more. By implementing an analytics-driven retail environment, organizations can make better decisions for procurement, marketing, merchandising, and other operational considerations. This, in turn, enables retailers to create a better buying experience and for identifying opportunities for organizational improvement. 

Some questions that we will answer in this blog include:

What are the benefits and importance of retail analytics?

What are some current trends in retail analytics?

How can AI impact retail analytics?

What are some challenges to effective retail analytics?

What are some common tools associated with retail analytics?

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