Data
Master Data Management: Best Practices & Real Life Examples in '24
There are many important types of data that companies use to improve their operations, such as product data, customer data, location data, or asset data.
In-Depth Guide to Data Versioning: Benefits & Formats in 2024
Companies rely on AI/ML models to make business decisions. Effective AI/ML models require high-quality data to make accurate predictions about future conditions. That’s why data is called the new oil for which successful companies need their own refinery. However, obtaining high-quality data is not a simple matter.
Data Annotation in 2024: Why it matters & Top 8 Best Practices
Annotated data is an integral part of various machine learning, artificial intelligence (AI) and GenAI applications. It is also one of the most time-consuming and labor-intensive parts of AI/ML projects. Data annotation is one of the top limitations of AI implementation for organizations.
Data Lake: What It Is, Benefits & Challenges in 2024
Data lakes have become one of the most popular repositories used to store large amounts of data. A study by Gartner shows that 57% of data and analytics leaders are investing in data warehouses, 46% are using data hubs and 39% are using data lakes.
All You Must Know About Data Curation in '24
Data curation is an important part of data management. Data curation is the process of collecting, wrangling and preserving data. It allows companies to store sustainable and accessible data to share and apply self-service analytics. Data-driven insights are crucial as data-driven sales strategies enable companies improve their sales productivity by 20 %.
Top 8 Data Masking Techniques: Best Practices & Use Cases in '24
Given the increasing cyber threats and implementation of data privacy legislation like the GDPR in the EU or CCPA in the US, businesses need to ensure that private data is used as little as possible.
Infonomics in 2024: What it is, Case Studies & Best Practices
Though IT and business leaders regularly state information is their most valuable asset, they fail to value or manage it like one. Data can be sold to monetization or organizations can use it to provide value-added services to their customers.
First Party Data: Use Cases & Best Practices in 2024
Your digital marketing can be only as targeted/powerful as the data it relies on. When customers interact with a brand, they leave behind first-party data. This data can help the organization deliver more personalized experiences for their customers. Organizations can trust these trails most since they are directly collected from the audience.
Data as a Service (DaaS): What, Why, How, Use cases & Tools in '24
Data as a service solutions help companies expose their data internally or externally. These solutions help companies monetize their data or democratize access to data and support analytics efforts What is Data-as-a-Service? Data-as-a-Service (DaaS) providers provide requested data to their consumers via m2m (machine-to-machine) interfaces.
What is a Data Catalog? How to build it, Best practices & Tools
Turning big data into actionable insights is a popular business goal. Data catalogs can help organizations achieve this goal. The purpose of a data catalog is to support a business to find, understand and maintain its existing data assets.