July, 2019

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Big Data Is Already A Thing Of The Past: Welcome To Big Data AI

Smart Data Collective

Not long ago, big data was one of the most talked about tech trends , as was artificial intelligence (AI). But, in case people need a reminder of how fast technology evolves , they only need to consider something newer — big data AI. It combines elements of both technologies. AI allows computers to perform cognitive functions, much like the human brain.

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Responsible Citizen Data Science. Yes, it is Possible.

DataRobot Blog

by Jen Underwood. To retain market leadership in the algorithm economy, enterprises require new ways to maximize the value of data and AI with citizen data scientists. Don’t think citizen data science is. Read More.

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7 Fundamental Steps to Complete a Data Project

Dataiku

It's hard to know where to start once you’ve decided that yes, you want to dive into the fascinating world of data and AI. Just looking at all the technologies you have to understand and all the tools you’re supposed to master is enough to make your dizzy.

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Waterfall to Agile: A Necessary Mindset Shift For Business Analysts

BA Learnings

I tend to describe the agile approach as a way of working; A targeted way of working that allows us to make changes, respond to customers’ needs and manage uncertainty with minimal delays, and without needing to wade through “red tape”. Agile manifesto encourages: - Customer collaboration over contract negotiation - Individuals and interactions over processes and tools - Responding to change over following a plan - Working software over full documentation This does not however imply that the agi

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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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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Data Lakes: What Are They and Who Needs Them?

Jet Global

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive. What was at first a data stream has morphed into a data river as enterprise businesses are harvesting reams of data from every conceivable input across every conc

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Descriptive Statistics and Data Visualization

TDAN

Turn Your Statistics Into Something More Interesting Data is quickly becoming a defining thing in the business world. It is the lifeblood of every company decision and thus, it defines what companies do. A company which doesn’t pay attention to proper statistics can be at a serious disadvantage from companies who do, especially companies that […].

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Business Intelligence vs. Automated Reporting: Which Do You Need?

Sisense

Blog. Both automated reporting and business intelligence can help businesses perform better but in different ways. With automated reporting, organizations can simply produce reports faster and with less effort from business data without further analysis. Alternatively, using a BI solution can offer ease of use in exploring the data, as well as scalability in automating reports from those explorations seamlessly and rapidly.

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A Data Science Leader’s Guide to Managing Stakeholders

Analytics Vidhya

Overview Managing the various stakeholders in a data science project is a must-have aspect for a leader Delivering an end-to-end data science project is. The post A Data Science Leader’s Guide to Managing Stakeholders appeared first on Analytics Vidhya.

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Your Ultimate Guide To Modern KPI Reports In The Digital Age – Examples & Templates

datapine

Experts predict that by 2025, around 175 Zettabytes of data will be generated annually, according to research from Seagate. Moreover, within just five years, the number of smart connected devices in the world will amount to more than 22 billion – all of which will produce colossal sets of collectible, curatable, and analyzable data, claimed IoT Analytics in their industry report.

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4 Data Goldmines Your Company Should Not Ignore

Smart Data Collective

In an earlier age, perhaps as little as a decade ago, businesses had to rely on intuition and educated guesses to guide their spending. The situation was famously captured by John Wanamaker, who said, “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.” Today, data is everywhere. Phones track our locations and our social media usage.

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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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The Power of Integrated Data and Analytics

Teradata

Integrated data and analytics has a proven track record of helping organize operations, enhance customer experience and improve revenue and market growth.

Analytics 104
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5 Questions you should be asking your data analysts.

Data Insight

What happens if we run that campaign? Who’s going to be affected if we make this change? How do we know what good looks like? Data can be a valuable asset, helping drive business effectiveness and decision-making. Yet businesses often fail to ask the right questions of their data in order to realise its ultimate potential. Here are the top five questions you should be asking your data analysts in order to get the most out of your data. 1.

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Using Business Intelligence in Demand Forecasting

Jet Global

With major advances being made in artificial intelligence and machine learning, businesses are investing heavily in advanced analytics to get ahead of the competition and increase their bottom line. One of those areas is called predictive analytics, where companies extract information from existing data to determine buying patterns and forecast future trends.

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Building a Recommendation System using Word2vec: A Unique Tutorial with Case Study in Python

Analytics Vidhya

Overview Recommendation engines are ubiquitous nowadays and data scientists are expected to know how to build one Word2vec is an ultra-popular word embeddings used. The post Building a Recommendation System using Word2vec: A Unique Tutorial with Case Study in Python appeared first on Analytics Vidhya.

Analytics 307
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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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14 Dashboard Design Principles & Best Practices To Enhance Your Data Analysis

datapine

The rise of innovative, interactive, data-driven dashboard tools has made creating effective dashboards – like the one featured above – swift, simple, and accessible to today’s forward-thinking businesses. In the digital age, there’s little need for a department of IT technicians, plus a qualified graphic designer, to create a dazzling data dashboard.

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Strategy, Leadership, Culture & Innovation: Interview with Cary Correia, GE USA: Part 1

Corinium

Drawing on over 30 years of experience, we caught up with our international keynote, Cary Correia, Chief Commercial Data Scientist, GE USA to share some golden nuggets on how to truly achieve a data-driven culture and become an intelligent enterprise. See how Cary’s teams worked towards a data driven culture, the use of proactive and reactive analytics, and facilitating the most significant steps to move from strategy to execution.

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Tools for machine learning development

O'Reilly on Data

The O'Reilly Data Show: Ben Lorica chats with Jeff Meyerson of Software Engineering Daily about data engineering, data architecture and infrastructure, and machine learning. In this week's episode of the Data Show, we're featuring an interview Data Show host Ben Lorica participated in for the Software Engineering Daily Podcast , where he was interviewed by Jeff Meyerson.

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Big Data, Machine Learning and Alteryx Inspires 2019

David Menninger's Analyst Perspectives

Alteryx Inspire 2019, this year's user conference for Alteryx, drew around 4500 customers, partners, and prospects to Nashville’s Gaylord Opryland Resort & Convention Center in Tennessee last month. The strong attendance was a reflection of the strong growth Alteryx has experienced over the last year; roughly 50% growth year-over-year. This year's conference focused on Alteryx's evolution from data preparation to AI and machine learning, and both were front and center.

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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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Glossary of Digital Terminology for Career Relevance

Rocket-Powered Data Science

Career Relevance. Definitions of terminology frequently seen and used in discussions of emerging digital technologies. (NOTE: This page is a WIP = Work In Progress.). AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data).

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Introduction to PyTorch-Transformers: An Incredible Library for State-of-the-Art NLP (with Python code)

Analytics Vidhya

Overview We look at the latest state-of-the-art NLP library in this article called PyTorch-Transformers We will also implement PyTorch-Transformers in Python using popular NLP. The post Introduction to PyTorch-Transformers: An Incredible Library for State-of-the-Art NLP (with Python code) appeared first on Analytics Vidhya.

Analytics 307
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Top 18 Social Media KPIs & Metrics You Should Use For A Complete SM Strategy

datapine

In a hyper-connected digital world driven by data, there has never been a better time for businesses to gather meaningful insights on their target prospects, in addition to measuring ongoing levels of commercial growth and performance. The modern consumer, or digital native, craves a significant level of value from the brands in which they’re looking to invest – and as such, to gain consumer loyalty, businesses must reach out and talk to their customers on a personal level.

Metrics 219
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African Customer Experiences With Theory U

Corinium

Africa is at the centre of a global development crisis and customer experience professionals have the opportunity to influence economic growth and increase shareholder value with meaningful impact. The 2030 Agenda for Sustainable Development, adopted by all United Nations Member States in 2015, provides a shared blueprint for peace and prosperity for citizens, businesses and the planet, now and into the future.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Managing machine learning in the enterprise: Lessons from banking and health care

O'Reilly on Data

A look at how guidelines from regulated industries can help shape your ML strategy. As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operation

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Embedded Data and Information Builders Summit 2019

David Menninger's Analyst Perspectives

Summit 2019, Information Builders' annual user conference, drew about 1000 attendees this year, including customers, partners and prospects all working with Information Builders' technologies. Under new leadership, Summit 2019 showcased the direction Information Builders is moving in the next couple of years.

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Ten more random useful things in R you may not know about

KDnuggets

I had a feeling that R has developed as a language to such a degree that many of us are using it now in completely different ways. This means that there are likely to be numerous tricks, packages, functions, etc that each of us use, but that others are completely unaware of, and would find useful if they knew about them.

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The Ultimate List of Popular Machine Learning Use Cases in our Day-to-Day Life

Analytics Vidhya

Overview We are the in middle of a golden age of machine learning applications Here’s a comprehensive list of popular and common machine learning. The post The Ultimate List of Popular Machine Learning Use Cases in our Day-to-Day Life appeared first on Analytics Vidhya.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

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Master Salesforce Reports With Modern Reporting Tools – Examples And Templates

datapine

In a data-driven age, modern organizations need access to advanced data analytics solutions to help them improve the business in a wealth of key areas—Salesforce is one of those solutions. One of the world’s most popular cloud-based customer relationship management (CRM) platforms, the software is designed to help companies across sectors plan and optimize their sales processes.

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Shifting towards a more customer focused culture

Corinium

What is the biggest challenge you face within your role today and how are you looking to tackle it? I think a challenge faced by many more traditional organisations (including our own) is how to put a financial value on Customer Experience. Traditionally business cases are built on the financial value that can be derived from an initiative with specific expectations around pay-back time frames.

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Acquiring and sharing high-quality data

O'Reilly on Data

The O’Reilly Data Show Podcast: Roger Chen on the fair value and decentralized governance of data. In this episode of the Data Show , I spoke with Roger Chen, co-founder and CEO of Computable Labs , a startup focused on building tools for the creation of data networks and data exchanges. Chen has also served as co-chair of O'Reilly's Artificial Intelligence Conference since its inception in 2016.

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Data Science at The New York Times

Domino Data Lab

Chris Wiggins , Chief Data Scientist at The New York Times, presented “Data Science at the New York Times” at Rev. Wiggins advocated that data scientists find problems that impact the business; re-frame the problem as a machine learning (ML) task; execute on the ML task; and communicate the results back to the business in an impactful way.

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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.