Anyone who’s spent time in the analytics trenches knows that reading about data frameworks is one thing – building dashboards that influence boardroom decisions is another beast entirely. While the white papers and conference talks have their place, real impact happens on the ground, where teams are wrestling with messy datasets, inconsistent reporting tools, and ever-shifting […]
How Self-Service Analytics Reduces Dependence on Data Teams
A self-service analytics tool should allow non-technical team members to explore analytical data, even without prior experience with business intelligence tools or knowledge of the underlying data. It should have an intuitive interface, allowing users to explore and visualize data in various ways to gain relevant insights. By no means should it require assistance from […]
My Career in Data Season 3 Episode 4: Michael Meyer, Solutions Engineer, Snowflake
Welcome back to an all new season or My Career in Data – a DATAVERSITY Talks podcast where we sit down with professionals to discuss how they have built their careers around data. This episode we speak with Michael Meyer, Solutions Engineer at Snowflake, about how he turned his early interest in weather to a […]
Mastering Data Visualizations for Better Understanding
The sheer volume of data generated daily has reached staggering levels, and approximately 328.77 million terabytes of data are created every single day, according to Statista. In fact, 90% of the world’s data has been created in just the past two years, underscoring the rapid pace of data generation. However, the explosion of data has […]
It’s Essential – Verifying the Results of Data Transformations (Part 2)
Test cases, data, and validation procedures are crucial for data transformations, requiring an understanding of transformation requirements, scenarios, and specific techniques for accuracy and integrity. Data transformations require complex testing due to their sophisticated logic, computations, and dependency on real-time data streams. This necessitates extensive test case design, representative data, automation tools, and robust validation […]
Predictive Analytics Techniques
The process of predictive analytics has three main steps: defining the objectives, collecting relevant data, and developing a predictive model using sophisticated algorithms. These models are further tuned for greater accuracy before being applied to real-world situations like risk analysis or fraud detection. Predictive analytics techniques are at the forefront of modern data science, enabling organizations to […]
How Organizations Can Overcome Barriers to Leveraging Real-Time Data
Digital-first businesses are managing an overwhelming amount of data, and many are struggling to make sense of it all and turn it into meaningful and actionable insights. Customers want fast and more personalized experiences at their fingertips, and real-time analytics is a key tool that companies can use to deliver tailored and responsive user experiences […]
4 Key Reasons to Build a Data Culture
Understanding the importance of data culture requires recognizing its pivotal role in shaping how organizations operate and innovate. A strong data culture instills a mindset where decisions are driven by data, fostering an environment that values evidence over intuition. This cultural shift enables organizations to harness the full potential of their data assets, leading to […]
Women in Data: Meet Rosaria Silipo
The latest installment in our Q&A series with women leaders in data features Rosaria Silipo, head of data science evangelism at KNIME. (Read our previous Q&A here.) Rosaria Silipo, Ph.D., has worked in data analytics and data science for the past 30-plus years. Currently the head of data science evangelism at KNIME (as well as a longtime DATAVERSITY […]
Harnessing Data: From Resource to Asset to Product
Companies that are data-driven demonstrate improved business performance. McKinsey says that data and analytics can provide EBITDA (earnings before interest, taxes, depreciation, and amortization) increases of up to 25% [1]. According to MIT, digitally mature firms are 26% more profitable than their peers [2]. Forrester research found that organizations using data are three times more […]