Pyramid Analytics has been recognized as a Visionary [Access the Report.](https://www.pyramidanalytics.com/gartner-magic-quadrant-2023/)
Pyramid Analytics has been recognized as a Visionary [Access the Report.](https://www.pyramidanalytics.com/gartner-magic-quadrant-2023/)

Machine Learning

What is machine learning?

We hear a lot about machine learning. But what is machine learning (ML), and how do I know if my organization uses it correctly in our workflows and processes?

Machine learning is a subset of artificial intelligence (AI). It is a type of artificial intelligence that uses data and algorithms to imitate how humans learn. Using statistical methods and techniques, humans create algorithms that can be trained to classify data or make predictions from uncovering key insights.

In the context of decision intelligence, this expands to include all automatic tasks and programs built to find new patterns and information buried in data.

It includes tools for:

  • Heuristics, which allow for immediate solutions to make decisions.
  • Automated data mining, is the analysis of data using a repeatable process.
  • Predictive analysis, provides technology to anticipate outcomes.
  • Deep learning, assumes the intelligence of a human.
  • AI, which mimics human behavior in the context of data and its analysis.

The benefit of ML is that data scientists and other business people can use and manipulate data sources to improve and enhance the models that have been built continually. Importantly, the models are self-improving‒they continually evolve and improve over time.

What are the use cases for machine learning?

Machine Learning has many use cases. According to Forbes, some of the top use cases involve:

  1. Data / Personal Security. This use case aids against malware and security events. In essence, we are safer and more secure as ML looks for patterns in breaches and infections.
  2. Financial Trading. There are a lot of financial upsides to using ML for market trades. If you use predictive analytics, and if the speed of execution exceeds what humans are capable of, the possibilities are endless.
  3. Personal Health. For most people, nothing is more important than being healthy. With ML, you can more accurately predict future outcomes by analyzing what has already happened.
  4. Marketing and Sales. Machine learning helps businesses market and sell their products to the correct people. Using ML, marketers can send personalized messages and targeted suggestions to buyers that find that specific offer useful.
  5. Natural Language Processing. ML helps in data discovery. Business people or analysts can ask questions using simple English expressions and have the machine appropriately interpret them to convey the relevant information quickly.

How would my business leverage ML?

According to TechTarget, machine learning is a “competitive differentiator.” Using ML, organizations can separate themselves from their competitors, improve sales, and increase market share. Machine learning can drive efficiency and value for organizations and their employees.

ML can help B2C organizations track consumer behavior. They can more easily generate insights on what buyers are purchasing, why they are buying, and where they are buying. This sharpens processes such as supply chain, warehousing, and transportation to minimize waste and maximize profits.

ML can help B2B organizations contact customers by intuitively measuring their activity and anticipating when they are ready to buy. Technology companies can detect patterns by tracking usage online and examining what messages buyers respond to.

How can Pyramid Analytics help me with machine learning?

Pyramid facilitates widespread machine learning adoption and usage. The Pyramid Decision Intelligence Platform lets people with varying analytical skills deploy ML functions and libraries against their own data sets to auto-discover information, make predictions, find patterns, and ultimately make better decisions.

With the push to incorporate machine learning into analytics, the need for a robust ETL is now crucial because most ML processes should not be executed on post-model data. The Pyramid Decision Intelligence Platform helps data scientists, data wranglers, and even business analysts build real-world machine learning logic and algorithms directly on source data so that ML can provide the most value for the organization.

Our vision is to automate the decision-making process and empower anyone to make faster, more intelligent decisions. Contact us for a demonstration to see how we integrate machine learning into our platform.