Data
Audio Annotation in 2024: What is it & why is it important?
In 2020, the market capitalization of AI/ML was $22.59 billion and is expected to reach $125 billion, growing at about 40% per year. Supervised and human-in-the-loop ML models make successful predictions if they have high-quality labeled/annotated data, as both models learn reality via the categorization of humans.
7 Best Data Migration Tools & Best Practices for a Successful Implementation
Data migration is the process of moving data from a data source to a target location. However, moving data to a new platform can lead to data loss or data quality issues as it is a complex and time-consuming process and requires multiple technologies.
Data Migration: Types, Best Practices & Strategies in '24
Some business projects require moving data from one source to a new data center, applications, or systems. However, moving data to a new platform can lead to data loss or data quality problems as it is a complex and time-consuming process and requires multiple technologies.
Data Fabric 2024: Modern Data Integration Components Guide
In this article, we explain data fabric for executives who need agile data pipelines for business intelligence.
Data Lineage: Techniques, Best Practices & Use Cases in 2024
Data and data-driven decision making are critical for business success. To rely on data in decisions, businesses need to understand where the data comes from, how it is processed and transformed. However, tracking the flow of data from source to destination can be complex.
Data Quality Assurance: Importance & Best Practices in 2024
Optimal decisions require high-quality data. High-quality data means data that represents its underlying real-world phenomena correctly. To achieve high data quality and sustain it, companies must implement data quality assurance procedures. This article explains what data quality assurance is, why it is essential, and the best practices for ensuring data quality.
Top 10 Training Data Platforms of 2024: In-depth Guide
Data is an essential part of the decision-making processes in today’s enterprises. Supervised AI/ML models require high-quality data to make accurate predictions. Training data platform tools ensure effective use of data processing from start to finish of ML deployment.
In-Depth Guide to Data Commercialization in 2024
Companies in every industry use data to create value and manage data as an asset. They collect and analyze huge amounts of data coming from various sources. The increasing availability of data enables businesses to make real-time decisions.
Top 20 Data Labeling Tools: In-depth Guide in 2024
For performing data labeling, companies need a data labeling tool. There are different data labeling tools, each with its own advantages and disadvantages. In this article, we classify them to help companies choose the most suitable one.
5 Ways to Enable Business Agility with Data Monitoring in '24
Data is an important guide for businesses to make data-driven decisions and get a realistic view of the industry they operate in. Data consistency is critical for analyzing and observing the status of businesses. That’s where data monitoring comes in. It offers businesses the opportunity to continuously check the quality of their data.