Sign up for our newsletter and get the latest big data news and analysis.

dbt Labs Report – Opportunities and Challenges for Analytics Engineers

The practice of analytics engineering (made popular by dbt Labs) took the data world by storm last year as the novel approach changed how data professionals work. Today, dbt Labs officially launched the inaugural State of Analytics Engineering report. The report assessed the analytics engineering practice and gathered insights from those actively involved in the day-to-day of data. 

MIT Experts on What You Need to Know Now about Data Analytics

In a new series, “The Analytics Edge,” published by MIT Sloan School of Management’s Ideas Made to Matter, MIT Sloan faculty, alumni, and industry experts share practical tips for developing and cultivating a strong analytics practice designed to give companies and organizations a distinct advantage for the future.

Podcast: Advances In Sports Analytics: Beyond Moneyball 

When Moneyball was released 20 years ago, audiences could not have imagined the strides data scientists would make in sports analytics in the years to come. In the latest UVA Data Points podcast, expert data scientists discuss how machine learning, wearable technology and computer vision are impacting the future of athlete health and sports analytics.   

Report: Audit Industry Rising to the Data Analytics Challenge

With businesses facing the strongest economic headwinds in years, the Chartered Institute of Internal Auditors (Chartered IIA) is urging internal auditors to embrace data analytics to navigate more risky, uncertain, and volatile times ahead. The new report, “Embracing data analytics: Ensuring internal audit’s relevance in a data-led world,” from Chartered IIA in partnership with AuditBoard aims to encourage internal audit to fully embrace data analytics and support the organization in doing the same.

With Sustainability Analytics, Big Data Can Save the World

In this contributed article, Cashion “Cash” East, Director of Analytics for Higg, discusses how sustainability analytics requires a lot of data from many different sources. Some of that data already exists and is standardized, while other data is coming from new sources with no established standards. In order for companies to collect and organize ESG data in a meaningful and efficient way, the article recommends that companies start doing five things as they begin building out their sustainability insights platform.

Cinchy Study Details How Dataware Eliminates Data Integration and Revolutionizes Application Development and Analytics

Cinchy, the dataware vendor that’s changing the way organizations work with data, released “The Rise of Dataware: An Integration-Minimizing Approach to Data,” a comprehensive analyst report that highlights a fundamental shift taking place in the data management sector. It focuses on a distinctive architectural approach that redefines the relationship between data and applications, and essentially eliminates the need for data integration as we know it.

Tomorrow’s Tech: What Does the Future of Analytics Look Like?  

In this contributed article, Nitin Aggarwal, Vice President of Analytics and Data Science for The Smart Cube, suggests that when it comes to analytics tech, it’s all about speed to insight. People are trying to make sure data is available in almost real-time across the business, which takes a lot of processing power and investment in infrastructure. Then once that data is ingested, people want to make it faster.

Data Fusion and Analytics for Chief Investigators: Survey Report, August 2022

Our friends over at Cognyte have a second survey on data fusion and analytics – this time for chief investigators. In their last survey, the 2022 IT leaders in the Data Fusion/Analytics Domain, the company spoke to CIOs and IT executives about their challenges and investment priorities for data fusion.

Using Advanced Analytics to Address Patient Risk and Deliver Value-based Care

In this contributed article, Michael Dulin, MD, PhD, Chief Medical Officer, Gray Matter Analytics, suggests that to improve health outcomes and lower cost, the U.S. healthcare system must abandon fee for service models and provide comprehensive, proactive value-based care (VBC). High-quality data and advanced analytics that produce actionable insights into patients’ medical and social needs are an essential building block for this transition. 

The Biggest Challenges When Adopting Data and AI Technologies

In this contributed article, David Sweenor, Senior Director of Product Marketing at Alteryx, explains what it takes to create a data-driven culture in the office. Taking small, incremental steps to developing a data-centric work culture is the way to go in the adoption of data science, ML, AI, and other technologies. It requires significant planning, reviewing, and customized development, but will ensure a dominant edge to any organization that does it right.