What is Machine Learning?
Industry experts, competitors, and even your customers are talking about machine learning and artificial intelligence. The terms, while used widely and interchangeably, are often misunderstood and carry a narrow definition. Both machine learning and artificial intelligence have distinct and practical applications for your business – not only driverless cars!
Machine learning is the process of building and training models to process data. In this capacity, your models are learning from your data to make better predictions. Artificial intelligence, consequently, uses these learnings to make a computer or technology stack act more human, apply learnings in an automated manner. In this way, Machine Learning allows computer systems to learn from data and make decisions without being explicitly programmed to do so.
Based on growing modern workloads, machine learning is understood to be a form of artificial intelligence and mainly refers to computers that can learn and improve their analysis on data over time without reprogramming their core logic. Related to machine learning, deep learning is a subset of machine learning involving artificial neural networks, inspired by the function and structure of a brain.
Acting as the brain of your business, machine learning needs data and information to process and learn from. In this way, the machine is designed to learn the instructions from a given dataset.
Data Transformation for Machine Learning
“Garbage in, Garbage out”
When it comes to machine learning, you need to feed your models good data to get good insights. Data in the real world can be really messy and in most cases, some sort of data cleansing needs to be performed prior to any data analysis. However, this can be a daunting task. Without the right technology stack in place, data transformation is time-consuming and tedious. Nevertheless, this is a critical step as it ensures maximum data quality which increases the accuracy of predictions. Based on our customers’ experiences, below are some common data transformations Matillion can help you with so your data can be processed within machine learning models.
- Remove Unused and Repeated Columns
- Change Data Types
- Handle Missing Data
- Remove String Formatting and Non-Alphanumeric Characters.
- Convert Categorical Data to Numerical
- Convert Timestamps
Machine learning can help your business process and understand data insights faster – empowering data-driven decisions to be made across your organization. For machine learning to be successful, however, your models will need to consume clean data sets. As the quality of your data increases, you can expect the quality of our insights to increase as well. Transforming data for analysis can be challenging based on the growing volume, variety, and velocity of big data. This challenge will need to be overcome to unlock the potential of your data and to mobilize your business to move faster and outpace competitors. When you are ready for machine learning, Matillion’s purpose-built data transformation for cloud data warehouses can help you increase the ROI on your data, transforming your data so it is machine learning ready!
Learn more about how Machine Learning can help your business gain a competitive advantage in our user guide.
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