Sat.Mar 16, 2019 - Fri.Mar 22, 2019

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Infographic: 11 Steps to Transition into Data Science (for Reporting / MIS / BI Professionals)

Analytics Vidhya

Introduction Do you often work with reports in Excel? Or regularly build dashboards and visualizations in Tableau or Power BI? If you answered yes. The post Infographic: 11 Steps to Transition into Data Science (for Reporting / MIS / BI Professionals) appeared first on Analytics Vidhya.

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Automating ethics

O'Reilly on Data

Machines will need to make ethical decisions, and we will be responsible for those decisions. We are surrounded by systems that make ethical decisions: systems approving loans, trading stocks, forwarding news articles, recommending jail sentences, and much more. They act for us or against us, but almost always without our consent or even our knowledge.

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Analytics By Design, For The Analytics Win

Rocket-Powered Data Science

We hear a lot of hype that says organizations should be “ Data – first ”, or “AI- first , or “ Data – driven ”, or “ Technology – driven ”. A better prescription for business success is for our organization to be analytics – driven and thus analytics-first , while being data -informed and technology -empowered. Analytics are the products, the outcomes, and the ROI of our Big Data , Data Science, AI, and Machine Learning investments!

Analytics 193
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Evaluating Vendors’ Mobile Business Intelligence and Analytics

David Menninger's Analyst Perspectives

I am happy to share some insights gleaned from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Mobile Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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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8 Excellent Pretrained Models to get you Started with Natural Language Processing (NLP)

Analytics Vidhya

Introduction Natural Language Processing (NLP) applications have become ubiquitous these days. I seem to stumble across websites and applications regularly that are leveraging NLP. The post 8 Excellent Pretrained Models to get you Started with Natural Language Processing (NLP) appeared first on Analytics Vidhya.

Modeling 292
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Proposals for model vulnerability and security

O'Reilly on Data

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. A recent flourish of posts and papers has outlined the broader topic, listed attack vectors and vulnerabilities, started to propose defensive solutions, and provided the necessary framework for this post.

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Get Your Analytics and Business Intelligence Any Time

David Menninger's Analyst Perspectives

For analytics to be effective, they need to be available to line-of-business personnel as needed in their normal course of conducting business, which today means providing rich mobile access to analytics through phones and tablets to support a mobile workforce seeking to conduct business in any location at any time. Workers today expect these mobile capabilities, which means organizations must make choices to provide analytics and BI platforms that can deliver them.

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DataHack Radio #20: Building Interpretable Machine Learning Models with Christoph Molnar

Analytics Vidhya

Introduction How do we build interpretable machine learning models? Or, in other words, how do we build trust in the models we design? This. The post DataHack Radio #20: Building Interpretable Machine Learning Models with Christoph Molnar appeared first on Analytics Vidhya.

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Take Complete Charge Of Customer Satisfaction Metrics – Customer Effort Score, NPS & Customer Satisfaction Score

datapine

“There’s a certain way of creating a service, hospitality, and experience that perpetuates people feeling like they matter.” – Julie Rice, entrepreneur, and investor. Today’s tech-savvy customers are driven by experiences. Now more than ever, consumers look for trust, honesty, transparency, value, and an exemplary level of customer experience (CX) from brands they’re willing to invest in.

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Sensor Analytics on Big Data at Micro Scale

Rocket-Powered Data Science

We often think of analytics on large scales, particularly in the context of large data sets (“Big Data”). However, there is a growing analytics sector that is focused on the smallest scale. That is the scale of digital sensors — driving us into the new era of sensor analytics. Small scale ( i.e., micro scale) is nothing new in the digital realm.

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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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Complete ML Study Path On Github

Data Science 101

Recently updated, is the March 2019 Machine Learning Study Path. It contains links and resources to learn Tensorflow and Scikit-Learn. If you are interested in details on the study path and how to best use the resources. There is a livestream on Facebook, Sunday March 17 on the Math for Data Science Facebook page.

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Announcing Domino 3.3: Datasets and Experiment Manager

Domino Data Lab

Our mission at Domino is to enable organizations to put models at the heart of their business. Models are so different from software — e.g., they require much more data during development, they involve a more experimental research process, and they behave non-deterministically — that organizations need new products and processes to enable data science teams to develop, deploy and manage them at scale.

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Take Advantage Of Mobile Dashboards – Examples & Selected Designs

datapine

We live in a mobile world. According to the statistics portal Statista , there are currently around 4.78 billion mobile device users worldwide. No longer are we bound by the shackles of cumbersome desktop PCs or one specific geographical location to conduct research or complete online data analysis or other important online tasks. In this hyperconnected age, it’s possible to connect, campaign, and produce from anywhere you may be in the world – and the mobile revolution is responsible for this s

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5 Advantages of Using a Redshift Data Warehouse

Sisense

Choosing the right solution to warehouse your data is just as important as how you collect data for business intelligence. To extract the maximum value from your data, it needs to be accessible, well-sorted, and easy to manipulate and store. Amazon’s Redshift data warehouse tools offer such a blend of features, but even so, it’s important to understand what it brings to the table before making a decision to integrate the system.

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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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Interview with Sriram Iyer @ CDAOI UK 2019

Corinium

Big Data 150
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March Madness: How to Up Your Game by Building a Better Bracket

DataRobot

The 2019 NCAA March Madness tournament has arrived! This is one of the most famous annual sports events in the United States, bringing together the best Division 1 men’s and women’s college basketball teams from 68 schools to compete against each other for the NCAA Champion title.

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Trends in Data Management and Analytics

TDAN

Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years. The emergence of various new concepts, technologies, and applications such as Hadoop, Tableau, R, Power BI, or Data Lakes indicate that changes are under way. Which concepts will be forgotten in five years and which […].

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Enhance your Lending with Predictive Analytics

BizAcuity

An unsecured loan is a loan issued and supported solely by the borrower’s creditworthiness, rather than by any kind of collateral. The terms of such loans, including approval and receipt, are therefore most often contingent on the borrower’s credit score. The consumer lending business is centered on the notion of managing the risk of borrower default.

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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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Compare All Jet Global Products in One Epic Webinar!

Jet Global

The key to making accurate, profitable decisions at the speed of business is complete data access and control. That simple concept is the premise of all of our product development. Why? Because at Jet Global, we believe in empowering everyday business users to become instantly successful and productive in an environment that is both user-friendly and secure.

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What To Know About The Importance Of Analytics In Content Marketing

Smart Data Collective

Among the various factors that play a role in the content marketing decision-making process, analytics ranks near the top of the list. However, not many people understand the benefits of using various analytics tools for marketing a business. Two Experts Share their Perspective on the Benefits of Analytics in Marketing. Elissa Hudson has covered the importance of analytics in digital marketing in her post for HubSpot.

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Teradata Has Been Named One of the World's Most Ethical Companies 2019

Teradata

Teradata is thrilled to be named one the of the World’s Most Ethical Companies, for the tenth consecutive year.

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Build A Recommendation Engine in One Day

Dataiku

The recommendation system topic in machine learning has been extensively documented; nowadays, you can find information ranging from the very basic to the cutting-edge (we’ve written our fair share about the topic too - including not one , not two , but three articles on beer recommendation engines alone).

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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.

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What’s Business Process Modeling Got to Do with It? – Choosing A BPM Tool

erwin

With business process modeling (BPM) being a key component of data governance , choosing a BPM tool is part of a dilemma many businesses either have or will soon face. Historically, BPM didn’t necessarily have to be tied to an organization’s data governance initiative. However, data-driven business and the regulations that oversee it are becoming increasingly extensive, so the need to view data governance as a collective effort – in terms of personnel and the tools that make up the strategy – is

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Viva Las Vegas: Join us at Directions North America 2019!

Jet Global

If it seems as though we were recapping the largest Microsoft Dynamics NAV, Business Central, and GP partner event just months ago, you are right. New for 2019, Directions North America is now a Spring event, and we’re excitedly preparing for one of our favorite shows of the year, taking place in Las Vegas, Nevada May 5th – May 8th. As a Gold Sponsor, we’re going all in on what has led us to success – our loyal partners!

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Don’t wait to set your data strategy as Netezza goes end of support

IBM Big Data Hub

Support for Netezza TwinFin and Striper models will end as early as June 2019, potentially leaving business-critical data in unsupported environments. Yet there’s no need for long-time Netezza customers to take those risks. The next stage in Netezza’s evolution has already arrived.

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Skills and Tools Every Data Engineer Needs to Tackle Big Data

Sisense

As a company that touts the benefits of a full end-to-end BI solution, we certainly know the value of a data engineer. The data engineer’s job is to extract, clean, and normalize data, clearing the path for data scientists to explore that data and build models. To do that, a data engineer needs to be skilled in a variety of platforms and languages. In our never-ending quest to make BI better, we took it upon ourselves to list the skills and tools every data engineer needs to tackle the ever-grow

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

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

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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What Is Pervasive Data Intelligence?

Teradata

Chris Twogood explains Pervasive Data Intelligence and why it's important to large-scale enterprise businesses.

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How Big Data Has Impacted The Real Estate Industry

Smart Data Collective

Big data has made its way into virtually every industry. The real estate profession is no exception. Real estate professionals all over the world are benefiting from big data in a number of ways. CIO has published a very introspective article on eight companies that are using big data to disrupt the real estate industry. Here are some of the biggest benefits of big data for real estate.

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Your Metadata Will Not Govern Itself

TDAN

Metadata Governance is easiest to understand when you separate the term into its two parts – Metadata and Data Governance. Ask any organization that excels in metadata management (or provides thorough documentation of their data, information, and records) whether or not they govern their metadata and they will surely respond affirmatively. These organizations make certain […].

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How CTSI-Global Scales Their Embedded Analytics

Sisense

My involvement with Sisense started in mid-2015. I got in right at the buying cycle. As part of our continuing tech investments, CTSI-Global decided to incorporate modern BI technology to help shippers perform advanced forecasting and modeling through elegant and robust visualizations on top of the centralized shipping data we aggregate. I had the responsibility of building the new analytics deployment from the ground up and scaling it to the mature and robust business intelligence solution that

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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.