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Discover the potential of machine learning in data management and the remarkable benefits when automating tasks. Here we tell you how we implemented machine learning in Conciliac EDM.

Table of Contents:

• What is machine learning?
• What are the advantages of machine learning in data management?
• How do we use machine learning in Conciliac EDM?

What is machine learning?

Machine learning, also known as machine learning, is a subfield of computer science and a branch of artificial intelligence that focuses on the development of algorithms and techniques that allow computers to learn and improve automatically through experience, without being explicitly programmed for each specific task.

The main goal of machine learning is to enable machines to acquire knowledge, recognize patterns and make predictions or decisions based on data.

Instead of following precise instructions, machine learning algorithms can learn from available data, identifying relationships and structures that may not be obvious to humans.

To do so, it uses a variety of approaches, such as:

• Supervised learning, where models are trained using labeled examples;
• Unsupervised learning, where models find patterns and structures in the data without labels;
• Reinforcement learning, where models learn through interactions and rewards.

Thanks to these approaches, it is possible to apply it to a variety of actions, such as voice recognition, natural language processing, computer vision, medicine, finance, fraud detection and process optimization, among others.

By allowing machines to learn from data and improve with experience, machine learning has proven to be a powerful tool for solving complex problems and making data-driven decisions.

What are the advantages of machine learning in data management?

Machine learning offers several advantages for task automation and data management. Among them, we highlight:

1. 1. Improve efficiency and speed with machine learning

      Automating tasks that would normally require a lot of human time and effort is now much simpler. Machine learning algorithms can process large volumes of data and perform complex tasks in a much shorter time than humans.

   2. Adoption and adaptation is enhanced

      Machine learning algorithms can learn and adapt as they receive more data, thus fulfilling a feedback function. This allows automated systems to improve over time, optimizing their results and making them more accurate.

3. Data-driven decision making

   Because it uses real-time and historical data to make informed decisions, it significantly reduces reliance on decisions based on intuition or assumptions, and enables more accurate and objective decision making.

4. Reduces human error

   Automated tasks using machine learning are less subject to human error, such as fatigue, inattention or bias, which can improve the accuracy and quality of results.

5. Enables analysis of large data volumes

   Machine learning is especially useful for analyzing large volumes of data and finding patterns or trends that may be difficult for humans to detect. This can help identify valuable insights and make strategic decisions based on data.

6. Increases customizability and adaptability

   Machine learning models can be trained to adapt to individual user preferences and needs. This makes it possible to deliver personalized experiences and targeted recommendations in a variety of areas, such as customer service, marketing or inventory management.

7. Enables intelligent automation

   This means that it increases the ability of automated systems to learn autonomously, make decisions and adapt to changing situations, being able to automate even the most complex and variable tasks.

How do we use machine learning at Conciliac EDM?

For some time now, more and more companies need to properly manage data to automate tasks and get more out of them and the resources they invest in.

Conciliac EDM is the multifunctional and multipurpose platform that integrates an ecosystem of solutions with which companies can carry out all types of data reconciliation using a new generation of intelligent tools.

These tools are based on all fields of artificial intelligence, including machine learning. Based on this capability, the platform allows users to operate in a practically autonomous and fluid way, determining in a single step what information they have to process, how and when they want to obtain a report.

This reduces execution times from days to seconds, optimizes the accuracy of the results because the processes are automated. The implementation of machine learning enables learning that facilitates adoption for multiple tasks.

This is, without a doubt, a smart way to streamline processes to make intelligent decisions based on proper data management. Do you want to know how we would do it with your processes? Request a free demo now.