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Published August 17, 2023

Machine Learning and AI in Modern Data Warehouses

Learn how ML and AI are set to change how businesses use data warehouses to analyze hyperscale data sets.

By Ocient Staff

Data warehousing has been around for quite some time now, and it has become a crucial tool for businesses to store, manage and analyze data. But in recent years, the integration of artificial intelligence (AI) and machine learning (ML) within a data warehouse has opened up new possibilities to drive innovation and ultimately competitive advantage.

Modern data warehouses, like Ocient, have been built from the ground up to make previously infeasible use cases possible. Through this innovation, AI and ML have become core components or “first-class citizens” which is when a concept, programming language or framework is equal in importance and capability to the entire design of the system.

In this post, we’ll delve into what a data warehouse is, what AI and ML entail, and how they synergistically enhance the capabilities of a data warehouse like the Ocient Hyperscale Data Warehouse to provide actionable insights, more efficient data workflows and unlock new capabilities.

What is a Data Warehouse?

A data warehouse is a central repository that stores and consolidates large volumes of data from various sources within an organization. Its primary purpose is to provide a unified platform for data analysis and reporting, enabling decision-makers to make informed choices based on historical, current, and sometimes external data. Data warehouses structure and organize data in a way that supports efficient querying and reporting, making them essential tools for business intelligence.

What is Artificial Intelligence?

Artificial Intelligence refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, problem-solving, perception, and language understanding. AI enables systems to analyze data, learn from it, and make decisions or predictions based on that data without explicit programming.

What is Machine Learning?

Machine Learning is a subset of AI that involves the development of algorithms and statistical models that enable systems to improve their performance on a specific task through learning from data. In other words, machine learning algorithms allow computers to identify patterns and relationships in data and use those patterns to make predictions or decisions.

How AI and ML Work Within a Data Warehouse

Up until recently AI and ML may have been applied to datasets as part of experimentation by data scientist that may have been working in silos outside of shared technical infrastructure. That’s why recent innovation that allows for AI and ML techniques to be fully integrated into a data warehouse are emerging as powerful tools that enable new capabilities. When AI and ML techniques are integrated into a data warehouse, they transform it into a dynamic powerhouse for predictive analytics. Here’s how:

  1. Enhanced Data Processing: AI and ML algorithms can handle large volumes of data with greater efficiency and speed. By integrating these technologies, a data warehouse can process complex queries, optimize data retrieval, and perform advanced statistical analyses faster than traditional methods.
  2. Advanced Pattern Recognition: ML algorithms excel at recognizing patterns and anomalies within data. This ability is invaluable for identifying trends, correlations, and outliers that might go unnoticed with traditional analysis methods within a data warehouse.
  3. Predictive Modeling: AI and ML enable the creation of predictive models that forecast future outcomes based on historical data right in a data warehouse. Businesses can use these models to anticipate market trends, customer behavior, and other critical factors, thus aiding in strategic decision-making.
  4. Personalized Recommendations: Leveraging AI and ML, a data warehouse can generate personalized recommendations for customers. This is particularly useful for e-commerce platforms, streaming services, and any industry that relies on understanding user preferences.
  5. Automated Data Cleansing: Data quality is crucial for accurate analytics. AI-powered data warehouses can automate data cleansing and validation processes, ensuring that the insights derived are reliable and accurate.

How AI and ML Benefit Data Warehouse Users

The incorporation of AI and ML techniques into data warehousing brings several benefits to users:

  1. Actionable Insights: Users gain access to predictive analytics, enabling them to make informed decisions and strategic plans based on accurate forecasts.
  2. Efficiency and Speed: As mentioned above, AI and ML accelerate data processing, reducing the time required to derive insights from raw data.
  3. Data-Driven Decision-Making: Predictive analytics empowers users to base decisions on data-backed predictions, minimizing guesswork and intuition.
  4. Competitive Edge: Businesses that harness the power of AI and ML in their data warehousing gain a competitive advantage by staying ahead of market trends and customer preferences.
  5. Cost Savings: Automated data cleansing and analysis processes reduce the need for manual intervention, leading to cost savings in terms of time and resources.

How AI and ML Work Within the Ocient Hyperscale Data Warehouse

Ocient has been built from the ground up as a unified data platform with AI and ML capabilities as first-class citizens.

Our customers can perform ML operations on the same platform that they use to extract, transform, load and store data. While efficiency-focused innovations like our Compute Adjacent Storage Architecture™ (CASA) and Zero Copy Reliability™, Ocient solutions cost up to 80% less than the competition.

As data scientist and engineers prioritize using AI and ML to make business impact, there’s no need to pull data in between applications. Data teams can work directly in the database, or they can export data from Ocient directly to the tool(s) of their choice using built-in ODBC, JDBC, and Python connectors.

The integration of artificial intelligence and machine learning with data warehouses, like Ocient, are a game-changer for businesses seeking to unleash the full potential of their data.  As these technologies continue to evolve, the future of data warehousing is undeniably intertwined with the limitless possibilities offered by artificial intelligence and machine learning.

If you’d like to learn more about artificial intelligence and machine learning within Ocient, contact us today to see a demo.