September, 2019

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6 bits of advice for Data Scientists

KDnuggets

As a data scientist, you can get lost in your daily dives into the data. Consider this advice to be certain to follow in your work for being diligent and more impactful for your organization.

Metrics 111
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13 Analytics & Business Intelligence Examples Illustrating The Value of BI

datapine

Digital data, by its very nature, paints a clear, concise, and panoramic picture of a number of vital areas of business performance, offering a window of insight that often leads to creating an enhanced business intelligence strategy and, ultimately, an ongoing commercial success. Business intelligence steps up into this process by creating a comprehensive perspective of data, enabling teams to generate actionable insights on their own.

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4 Key Aspects of a Data Science Project Every Data Scientist and Leader Should Know

Analytics Vidhya

Overview A data-science-driven product consists of multiple aspects every leader needs to be aware of Machine learning algorithms are one part of a whole. The post 4 Key Aspects of a Data Science Project Every Data Scientist and Leader Should Know appeared first on Analytics Vidhya.

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Strategy is Unleashing the Potential of Enterprise Data

Corinium

Enterprises across the globe are waking up to the fact that data is an asset that requires its own strategy. Those that treat it as such are now seeing substantial returns on their investments.

Strategy 199
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Activating Intent Data for Sales and Marketing

Sales and marketing leaders have reached a tipping point when it comes to using intent data — and they’re not looking back. More than half of all B2B marketers are already using intent data to increase sales, and Gartner predicts this figure will grow to 70 percent. The reason is clear: intent can provide you with massive amounts of data that reveal sales opportunities earlier than ever before.

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Machine learning and analytics for time series data

O'Reilly on Data

The O’Reilly Data Show Podcast: Arun Kejariwal and Ira Cohen on building large-scale, real-time solutions for anomaly detection and forecasting. In this episode of the Data Show , I speak with Arun Kejariwal of Facebook and Ira Cohen of Anodot (full disclosure: I’m an advisor to Anodot). This conversation stemmed from a recent online panel discussion we did, where we discussed time series data, and, specifically, anomaly detection and forecasting.

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Conversational Computing and More News from Oracle Analytics Summit 2019

David Menninger's Analyst Perspectives

The Oracle Analytics Summit 2019 was the inaugural user event for Oracle Analytics customers, and they also broadcast the video for thousands of others. You can watch the keynote at [link]. Executives talked about some big organizational changes, including Bruno Aziza joining last year to lead the analytics organization. This event marked a transition and "a new beginning" for the Oracle Analytics portfolio, as the company announced three new analytics products.

More Trending

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Make Sure You Know The Difference Between Strategic, Analytical, Operational And Tactical Dashboards

datapine

The secret is out, and has been for a while: In order to remain competitive, businesses of all sizes, from startup to enterprise, need business intelligence (BI). Business intelligence has evolved into smart solutions that provide effective data management – from extracting, monitoring, analyzing, and deriving actionable insights needed to stay competitive on the market, to powerful visualizations created with a dashboard builder which enables business users to interact with data and drill into

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4 Unique Methods to Optimize your Python Code for Data Science

Analytics Vidhya

Overview Writing optimized Python code is a crucial piece in your data science skillset Here are four methods to optimize your Python code (with. The post 4 Unique Methods to Optimize your Python Code for Data Science appeared first on Analytics Vidhya.

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Are you treating your data as an asset? (Xero)

Corinium

Data as an Asset. I first heard the phrase “our data is one of our biggest assets” while working in the Munich headquarters of a multinational corporation. It had been uttered by one executive or other amid a talk full of content-free phrases that I had mostly tuned out, but being related to my area of expertise, this one caught what was left of my attention.

IT 30
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Understanding deep neural networks

O'Reilly on Data

The O’Reilly Data Show Podcast: Michael Mahoney on developing a practical theory for deep learning. In this episode of the Data Show , I speak with Michael Mahoney , a member of RISELab , the International Computer Science Institute , and the Department of Statistics at UC Berkeley. A physicist by training, Mahoney has been at the forefront of many important problems in large-scale data analysis.

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Revolutionize QA: GAPs AI-Driven Accelerators for Smarter, Faster Testing

GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.

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5G Roadmap: Preparing Your Enterprise Architecture

erwin

Why planning your 5G roadmap requires significant input from enterprise architects. 5G is coming and bringing with it the promise to transform any industry. And while the focus has been on the benefits to consumers, the effects on the enterprise are far- reaching. Few examples of emerging technology have the potential to disrupt and downright revolutionize certain markets and processes than 5G.

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Which Data Science Skills are core and which are hot/emerging ones?

KDnuggets

We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.

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Your Complete Guide To Creating Professional TV Dashboards

datapine

In the Age of Information, data equals power. By harnessing the power of your business’s most valuable digital insights, you will enhance decision-making, improve internal communication, and accelerate your success. But with so much information and such little time in the day, how do you get the most from your data? Data is most effective when it’s visual, easy to analyze, and accessible to everyone in the organization.

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A Data Scientist’s Guide to 8 Types of Sampling Techniques

Analytics Vidhya

Overview Sampling is a popular statistical concept – learn how it works in this article We will also talk about eight different types of. The post A Data Scientist’s Guide to 8 Types of Sampling Techniques appeared first on Analytics Vidhya.

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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The $7 billion Alternative Data Explosion

Corinium

Alternative data looks set to go mainstream. The term may have originally been used in reference to the non-traditional datasets hedge funds and investors use to get an edge on the markets. But the sheer variety of alternative datasets available today means its usage is quickly spreading to other industries and sectors.

Marketing 150
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Top 10 BI data visualization tools

CIO Business Intelligence

There is golden knowledge in the sea of data that businesses are swimming in. Being able to fish out the business intelligence you need — when you need it — is the key to steering your ship.

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A Long View on How Big Data and AI Have Transformed Business Culture

Bruno Aziza

Today, as data has become a lifeblood of industry leading firms, competing on analytics has become an unquestioned mantra, and firms have anointed Chief Data Officers to occupy the C-Suite.

Big Data 109
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12 Deep Learning Researchers and Leaders

KDnuggets

Our list of deep learning researchers and industry leaders are the people you should follow to stay current with this wildly expanding field in AI. From early practitioners and established academics to entrepreneurs and today’s top corporate influencers, this diverse group of individuals is leading the way into tomorrow’s deep learning landscape.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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How a Baby Boomer Became a Data Scientist at 60

DataCamp

You can become a data scientist at any age if you’re willing to put in the work.

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A Beginner-Friendly Guide to PyTorch and How it Works from Scratch

Analytics Vidhya

Overview What is PyTorch? How can you get started with it from scratch? We’ll cover all of that in this article PyTorch is one. The post A Beginner-Friendly Guide to PyTorch and How it Works from Scratch appeared first on Analytics Vidhya.

IT 307
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How to Become a Data-Driven Organization

Corinium

It might seem obvious that business decisions based on facts and data consistently deliver better results than those based on instinct or intuition. So, it should be no surprise that NewVantage Partners’ Big Data Executive Survey 2018 suggests that 99% of business leaders are trying to make their organizations more data-driven. What might be more surprising to some is that just a third of them are succeeding.

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Business Process Can Make or Break Data Governance

erwin

Data governance isn’t a one-off project with a defined endpoint. It’s an on-going initiative that requires active engagement from executives and business leaders. Data governance, today, comes back to the ability to understand critical enterprise data within a business context, track its physical existence and lineage, and maximize its value while ensuring quality and security.

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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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Power BI vs. Tableau: Self-service analytics tools compared

CIO Business Intelligence

Business intelligence (BI) and analytics platforms have long been a staple for business, but thanks to the rise of self-service BI tools, responsibility for analytics has shifted from IT to business analysts, with support from data scientists and database administrators.

Analytics 106
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10 Great Python Resources for Aspiring Data Scientists

KDnuggets

This is a collection of 10 interesting resources in the form of articles and tutorials for the aspiring data scientist new to Python, meant to provide both insight and practical instruction when starting on your journey.

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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. Strata attracts the leading names in the fields of data management, data engineering, analytics, ML, and artificial intelligence (AI).

IoT 21
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Everything you Should Know about p-value from Scratch for Data Science

Analytics Vidhya

Overview What is p-value? Where is it used in data science? And how can we calculate it? We answer all these questions and more. The post Everything you Should Know about p-value from Scratch for Data Science appeared first on Analytics Vidhya.

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Marketing Operations in 2025: A New Framework for Success

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

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3 reasons mobile business intelligence apps have minimal adoption in your business (and how to fix it)

Corinium

Instant noodles and the on-demand life. It’s no secret that, despite the huge movement toward sustainable living, we just can’t live without some things being instant. One such crutch for students worldwide and most of Asia’s young adult population (also the entire American prison system) are the ubiquitous instant noodles. 100 billion servings are eaten every year.

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Benefits of Data Vault Automation

erwin

The benefits of Data Vault automation from the more abstract – like improving data integrity – to the tangible – such as clearly identifiable savings in cost and time. So Seriously … You Should Automate Your Data Vault. By Danny Sandwell. Data Vault is a methodology for architecting and managing data warehouses in complex data environments where new data types and structures are constantly introduced.

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Coursera Course for AWS Machine Learning

Data Science 101

Amazon and Coursera have teamed up to create Getting Started with AWS Machine Learning. Topics covered are: Machine Learning. Computer Vision. NLP. Amazon Sagemaker. Happy Learning!

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Python Libraries for Interpretable Machine Learning

KDnuggets

In the following post, I am going to give a brief guide to four of the most established packages for interpreting and explaining machine learning models.

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Predicting the Future of Sales: How AI and Automation Will Revolutionize Strategies

In this exploration, we're diving into predictions about the future of sales. We're talking about a complete shake-up powered by automation and artificial intelligence (AI). These aren't just fancy tools — they're real game-changers. Automation and AI are here to redefine every interaction, making them smarter, faster, and more meaningful. From personalized customer journeys to streamlined sales processes, the goal is to make every moment count, enhancing both efficiency and connection.