Tag: Intelligence

The Future of Marketing is Creative

Research Desk

While marketing teams swim in a sea of data and information, the future depends on creativity. Establishing a culture of human ingenuity gives purpose to data intelligence, transforms your team, and elevates customer experience. Learn from experts who have already begun the shift—and develop your own five-point plan to embrace the future.

Six Things You Need to Know about Machine Learning to Be Successful

Research Desk

Today, the vast majority of organizations realize they need to digitally transform to compete. Many organizations want to accelerate this change, and data science tools such as machine learning are at the heart of this.

This checklist report by TDWI (Transforming Data with Intelligence) and sponsored by Snowflake focuses on six technology considerations for successful machine learning and data science.

The checklist will cover:

  • How organizations that utilize advanced techniques like machine learning are more likely to see an impact on their bottom line
  • Why you should consider a cloud data platform for data management
  • Tips to collecting and understanding the useful data needed to train a machine learning model
  • The importance of feature engineering
  • Key elements to deploying a machine learning model within your company

Six Considerations for Utilizing Cloud Data Platforms

Research Desk

Organizations today collect terabytes or even petabytes of diverse data from both internal and external sources. Much of it is produced in the cloud.

One approach gaining popularity for modern data management and analytics is to utilize a cloud data platform—a single integrated platform available on the cloud that houses diverse data and provides services such as a data warehouse, data lake, analytics, governance, and/or administrative tooling.

This checklist by TDWI (Transforming Data with Intelligence) and sponsored by Snowflake will cover:

  • An introduction to the cloud data platform and several important requirements
  • How it can help improve productivity, provide agility across workloads, and shorten time to value
  • How it provides one place to store and access data for analytics and other use cases
  • Details into the multiple workloads and data types a cloud data platform can support
  • How data can be stored in the warehouse or in a data lake, across multiple nodes and both can be part of the same platform