Thu.Oct 15, 2020

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12 Powerful Tips to Ace Data Science and Machine Learning Hackathons

Analytics Vidhya

Overview Data science hackathons can be a tough nut to crack, especially for beginners Here are 12 powerful tips to crack your next data. The post 12 Powerful Tips to Ace Data Science and Machine Learning Hackathons appeared first on Analytics Vidhya.

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Why the Single Source of Truth Paradigm in Data Warehousing is Outdated

Teradata

The old paradigm of the data warehouse serving as the single source of truth in today's ever evolving data landscape can no longer be sustained. Find out why.

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Enabling productivity and scale through improved enterprise knowledge management

CIO Business Intelligence

This article was co-written with Leila Dige. As the amount of knowledge generated within organizations continues to rise, firms must implement systems that make it easy for employees to find the information they need when they need it. Doing so not only stands to improve employee experience and boost productivity, but also can enable a level of agility and innovation that can become a competitive differentiator.

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Harnessing Streaming Data: Insights at the Speed of Life

Sisense

Blog. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. Streaming data analytics is expected to grow into a $38.6 billion market by 2025.

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Beyond the Basics of A/B Tests: Innovative Experimentation Tactics You Need to Know as a Data or Product Professional

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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Live Patching Is Invaluable To Data Development In Linux

Smart Data Collective

There are a number of different platforms for developing applications that rely on big data. Linux is unquestionably one of the most important. Computer Weekly has stated that Linux is the “powerhouse of big data.” However, developing big data applications rely on the most up-to-date tools. Live patching is one of the most important technologies for developers working on data analytics projects on Linux.

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AI Platforms in 2020 and Beyond: What to Look For

Dataiku

What is an AI platform? And when looking to invest in an AI platform in today’s economic climate, what are the must-have features?

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How-to: Index Data from S3 via NiFi Using CDP Data Hubs

Cloudera

About this Blog. Data Discovery and Exploration (DDE) was recently released in tech preview in Cloudera Data Platform in public cloud. In this blog we will go through the process of indexing data from S3 into Solr in DDE with the help of NiFi in Data Flow. The scenario is the same as it was in the previous blog but the ingest pipeline differs. Spark as the ingest pipeline tool for Search (i.e.

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The New Normal for FP&A: Forecasting

Jedox

For many organizations, the onset of the global health crisis has been like a bank of fog rapidly and unexpectedly engulfing a ship at sea. Suddenly your tried and true navigational skills and processes and the way you have always assessed risks and opportunities has been taken away from you. You must rely on new ways to pilot the ship to a safe port.

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How Employee Training In Enterprises Can Benefit From Data

Smart Data Collective

Enterprises now acknowledge the value of having a highly capable workforce. The ever-changing business landscape demands workers to continually upskill and reskill, giving rise to employee training utilization. Most organizations are now reinforcing their human resources and training and development departments to help them address the need. Large US companies on the average spent $17.7 million on such efforts in 2019.