Systems | Development | Analytics | API | Testing

Analytics

The Ultimate Guide to Retail Data Analytics

Whether you love, hate or remain indifferent towards data, it’s impossible to deny its importance in today’s business landscape. Businesses across all sectors and industries collect data and perform data analysis, to better understand their customers and business processes, in an effort to boost productivity, reduce expenditure and gain competitive advantage.

Improving LLM Accuracy & Performance - MLOps Live #28 with Databricks

Watch session #28 in our MLOps Live Webinar Series featuring Databricks where we discuss improving LLM accuracy & performance. Hear Margaret Amori (Databricks), Vijay Balasubramaniam (Databricks) , and Yaron Haviv (Iguazio) share best practices and pragmatic advice on successfully improving the accuracy and performance of LLMs while mitigating challenges like risks and escalating costs. See real examples including techniques to overcome common challenges using tools such as Databricks Mosaic AI and their new open LLM, DBRX.

Snowflake Data Clean Rooms for Marketing

In less than 5 minutes, Ankur Abhishek, Senior Product Manager at Snowflake, demostrates how Snowflake Data Clean Rooms can be used for audience overlap, audience lookalike, and attribution analysis. As Kamakshi Sivaramakrishnan, Senior Director of Product Management at Snowflake, explains, "This is the full marketing lifecycle brought in its entirety in a Snowflake clean room, run securely with multiple parties collaborating with each other. This is demystifying clean rooms.".

What is Data Preprocessing? Definition, Importance, and Steps

Did you know data scientists spend around 60% of their time preprocessing data? Data preprocessing plays a critical role in enhancing the reliability and accuracy of analytics. This blog will discuss why data preprocessing is essential for making data suitable for comprehensive analysis.

Data Integrity vs. Data Quality: Here's How They Are Different

Data integrity refers to protecting data from anything that can harm or corrupt it, whereas data quality checks if the data is helpful for its intended purpose. Data quality is a subset of data integrity. One can have accurate, consistent, and error-free data, but it is only helpful once we have the supporting information for this data. Data integrity and quality are sometimes used interchangeably in data management, but they have different implications and distinct roles in enhancing data usability.

Exposed: How Secure Are Your Embedded Analytics Really?

The ever-growing threat landscape of hackers, cyberattacks, and data breaches makes data security a top priority, especially when integrating analytics capabilities directly into customer-facing applications. To make informed decisions, it’s crucial to understand how embedded analytics platforms function from a security standpoint.

Logi Symphony Has You Prepared for New Cookie Restrictions

Embedding analytics into your application? New browser restrictions are on the way for Google Chrome that can block some third-party content that uses cookies from being accessible to users by default, in addition to restrictions in Safari and Firefox you may have already seen.