The Cost of Bad Data Practices A recent report by commercial data and analytics firm Dun and Bradstreet reveals that businesses are missing out on revenue opportunities and losing customers due to ineffective data practices. The research, based on a survey…
Unlocking the Power of Advanced Analytics in Retail: Overcoming the Barriers
Despite the well-documented benefits of advanced analytics, many retailers have been slow to fully embrace this powerful tool. In a recent study, the authors interviewed 24 global retail executives to uncover the primary reasons behind this reluctance. This article delves into…
How DoorDash Became the Dominant Food Delivery Service
DoorDash‘s journey from a small startup to the dominant player in the food delivery market is a remarkable story of strategic execution and data-driven innovation. This article delves into the three critical elements that fueled DD’s rise: a clear strategy and…
Riding the Data Wave: How Uber Transforms Transportation with Data Science
Uber leverages data science and BD to revolutionize transportation and logistics on a global scale. With over 8 million users, 1 billion trips, and 160,000 drivers across 449 cities in 66 countries, Uber has become a leading force in the ride-sharing…
How Netflix Leveraged Big Data to Boost Revenue by Billions
Netflix‘s remarkable success in the entertainment industry can be largely attributed to its strategic use of big data and analytics. With a market valuation exceeding $164 billion, Netflix has outpaced competitors such as Disney, thanks in part to a customer retention…
Navigating the Evolution of Data Systems: From Insights to Production
The landscape of data tools has dramatically shifted in the last decade, with new categories and frameworks emerging to meet the growing demand for data-driven insights. As businesses increasingly rely on data systems to inform their decisions, the evolution of data systems presents both unprecedented opportunities and significant challenges for data professionals. This article explores key trends shaping the future of data systems, examines their implications for organizations,…
Transforming Data Management: The Evolution of Change Data Capture at Airbnb
The need for dynamic data management has become increasingly critical in modern applications. This is particularly true for platforms like Airbnb, where real-time updates are essential for features such as dynamic pricing and availability management. The Challenge of Evolution As Airbnb’s…
Introducing DBLog: An Efficient Change-Data-Capture Framework for Real-Time Data Synchronization
Change-Data-Capture (CDC) is a method for capturing committed changes from a database in real-time and propagating those changes to downstream consumers. It is increasingly utilized to synchronize multiple heterogeneous datastores, such as MySQL and ElasticSearch, addressing challenges associated with traditional techniques…
The Future of the Modern Data Stack: Insights and Innovations
In the rapidly evolving landscape of data management, understanding the modern data stack is crucial for organizations aiming to leverage their data effectively. This blog explores the past, present, and future of the modern data stack, focusing on key innovations and…
Transforming Data Integration: The Shift from ETL to ELT in the Cloud Era
What You’ll Learn in This Blog ETL vs ELT Let’s start by understanding the difference between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform). ETL ETL emerged in the 90s with the rise of data warehousing. The process involved: Before…