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insideBIGDATA Guide to Big Data for Finance (Part 3)

[SPONSORED CONTENT] This insideBIGDATA technology guide co-sponsored by Dell Technologies and AMD, “insideBIGDATA Guide to Big Data for Finance,” provides direction for enterprise thought leaders on ways of leveraging big data technologies in support of analytics proficiencies designed to work more independently and effectively across a few distinct areas in today’s financial service institutions (FSI) climate.

insideBIGDATA Guide to Big Data for Finance (Part 2)

This insideBIGDATA technology guide co-sponsored by Dell Technologies and AMD, insideBIGDATA Guide to Big Data for Finance, provides direction for enterprise thought leaders on ways of leveraging big data technologies in support of analytics proficiencies designed to work more independently and effectively across a few distinct areas in today’s financial service institutions (FSI) climate.

Interview: Prat Moghe, CEO of Cazena

I recently caught up with Prat Moghe, CEO of cloud data lake leader Cazena to get his take on how getting off the ground with cloud data lakes continues to be a major frustration for enterprises. We’re seeing such deployments taking at least six months and millions of dollars of annual spend for in-house development and management. There’s got to be a better way. Gartner has estimated the failure rate of big data projects as high as 80%. What can you do about companies that stubbornly hang on to legacy data strategies, using analytics/BI approaches that put them ever-more behind competitors who are modernizing their data stack with AI/ML/etc? In this interview, we’ll get some valuable perspectives for you to follow in accelerating your time-to-analytics.

Interview: Unlocking Audience Understanding with NLP AI

I recently caught up with Andrea Vattani, Co-Founder & Chief Scientist, Spiketrap, to explore the path forward for brands looking to unlock true understanding of their audiences and their communications in the context of the world. Only two months into 2021 and nearing our second year of the pandemic, consumer behavior has changed rapidly and will continue to evolve as we adapt to new ways of life. So, how can brands keep a pulse on their shifting audiences this year and beyond?

Interview: Luminati CEO, Or Lenchner

I recently caught up with Or Lenchner, CEO at Luminati, to discuss his company’s Data Collector product, an automated data collection tool, allowing customers to collect the most accurate data at scale quickly, easily, and without getting blocked. The Data Collector integrates and automates all stages of the data collection process for customers but leaves them in full control over the data they collect.

Interview: Targeting is Becoming a Data Science Problem

I recently caught up with Miguel Araujo, Director of Data Science at Semasio, to explore the question: with the impending loss of the cookie and changing nature of tracking user IDs, what does the future of targeting look like? Moving forward, advertisers must reference and merge a plethora of user attributes to make predictions about target audiences. As such, the traditional boundaries of targeting will begin to erode — becoming more of a data science problem.

Video Highlights: COVID Data Community Profile Report

With the COVID-19 data now open to the public, the need for better analysis and aggregation of that information in the U.S. has skyrocketed. If you’re interested in learning more about the current trends impacting the nation and the data that backs it up, check out the Datapalooza COVID Data Community Profile video presentation below, hosted by data journalism firm, CareSet.

Databricks Launches SQL Analytics to Enable Cloud Data Warehousing on Data Lakes

Databricks, the data and AI company, announced the launch of SQL Analytics, which for the first time enables data analysts to perform workloads previously meant only for a data warehouse on a data lake. This expands the traditional scope of the data lake from data science and machine learning to include all data workloads including Business Intelligence (BI) and SQL.

Interview: Feature Stores for Machine Learning

In this interview, Mike Del Balso from Tecton and Willem Pienaar from Feast answer our questions and explain why feature stores are key to building machine learning models and deploying them to production to power new applications.

Interview: Andy Horng, Co-Founder and Head of AI, Cultivate

I recently caught up with Andy Horng, Co-Founder and Head of AI at Cultivate, to get a sense for the technology underlying the company’s AI-powered leadership development platform. NLP plays an important role, and as a result they’re using the RoBERTa language model for very good results.