May, 2019

Designing Charts and Graphs: How to Choose the Right Data Visualization Types

datapine

Modern dashboard software makes it simpler than ever to merge and visualize data in a way that’s as inspiring as it is accessible. But while doing so is easy, a great dashboard still requires a certain amount of strategic planning and design thinking.

Research quality data and research quality databases

Simply Statistics

When you are doing data science, you are doing research. You want to use data to answer a question, identify a new pattern, improve a current product, or come up with a new product.

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Moving from reactive analytics to proactive analytics

Corinium

Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year.

ABCs of Data Normalization for B2B Marketers

Data normalization. It’s not a far stretch to suggest that the topic isn’t exactly what gets marketers excited in their day-to-day workflow. However, if lead generation, reporting, and measuring ROI is important to your marketing team, then data normalization matters - a lot. In this eBook, we’ll break down the ins and outs of data normalization and review why it’s so critical for your marketing strategies and goals!

Statistics 101: Introduction to the Central Limit Theorem (with implementation in R)

Analytics Vidhya

Introduction What is one of the most important and core concepts of statistics that enables us to do predictive modeling, and yet it often. The post Statistics 101: Introduction to the Central Limit Theorem (with implementation in R) appeared first on Analytics Vidhya.

How Artificial Intelligence Will Disrupt the Financial Sector

DataFloq

Artificial intelligence thrives with data. The more data you have, the better your algorithms will be. However, just having a lot of data is not sufficient anymore.

More Trending

Five benefits of data analytics for your sales branches

Phocas

Your branches are the frontline of your business, leading the charge when it comes to customer interaction and building customer loyalty.

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4th Industrial Revolution, What is it? And What Impact does it Actually have?

Corinium

Industry 4.0…. it is just a buzz word thrown about? What does it actually mean? And how does it have an impact? We went straight to the source and asked the founding father and driving force behind the Industry 4.0 workgroup- Henrik von Scheel. What exactly is the Fourth Industrial Revolution

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Applications of data science and machine learning in financial services

O'Reilly on Data

The O’Reilly Data Show Podcast: Jike Chong on the many exciting opportunities for data professionals in the U.S. and China. In this episode of the Data Show , I spoke with Jike Chong , chief data scientist at Acorns , a startup focused on building tools for micro-investing.

10 Useful Data Analysis Expressions (DAX) Functions for Power BI Beginners

Analytics Vidhya

Introduction We have worked on plenty of drag-and-drop tools in our business intelligence (BI) journey. But none has come close to matching the Swiss. The post 10 Useful Data Analysis Expressions (DAX) Functions for Power BI Beginners appeared first on Analytics Vidhya.

How to Solve 4 Common Challenges of Legacy Information Management

Speaker: Chris McLaughlin, Chief Marketing Officer and Chief Product Officer, Nuxeo

After 20 years of Enterprise Content Management (ECM), businesses still face many of the same challenges with finding and managing information. Join Chris McLaughlin, CMO and CPO of Nuxeo, as he examines four common business challenges that these legacy ECM systems pose and how they can be addressed with a more modern approach.

A Guide to a Career In Big Data

DataFloq

Some might feel that data science is intimidating. This is particularly the case when someone is just getting started. They might wonder what tool should they start learning such as R or maybe Python. They may feel unsure about what techniques they should put the majority of their focus on.

Top 14 Must-Read Data Science Books You Need On Your Desk

datapine

“Big data is at the foundation of all the megatrends that are happening.” – Chris Lynch, big data expert. We live in a world saturated with data. At present, around 2.7

The Internet of Things: Real-Time Data and Analytics Enable Business Innovation

David Menninger's Analyst Perspectives

The emerging internet of things (IoT) is an extension of digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere.

Snowflake: 3 Benefits of a Self-Adapting Data Warehouse

Corinium

With the rise of new data streams, the ability to access more data and derive insights from it more quickly is critical. By 2023, worldwide revenue for big data solutions will reach $260 billion.*

The 2019 Technographic Data Report for B2B Sales Organizations

In this report, ZoomInfo substantiates the assertion that technographic data is a vital resource for sales teams. In fact, the majority of respondents agree—with 72.3% reporting that technographic data is either somewhat important or very important to their organization. The reason for this is simple—sales teams value technographic data because it makes essential selling activities easier and more efficient.

Sustaining machine learning in the enterprise

O'Reilly on Data

Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning. Continue reading Sustaining machine learning in the enterprise

Data Science Project: Scraping YouTube Data using Python and Selenium to Classify Videos

Analytics Vidhya

This article was submitted as part of Analytics Vidhya’s Internship Challenge. Introduction I’m an avid YouTube user. The sheer amount of content I can. The post Data Science Project: Scraping YouTube Data using Python and Selenium to Classify Videos appeared first on Analytics Vidhya. Machine Learning Python classification data collection Data Extraction machine learning python random forest scraping selenium web scraping

IoT in e-Commerce: How a Connected World Can Change Trade

DataFloq

The Internet of Things is one of the hottest topics today that penetrates all spheres of life from healthcare to commerce.

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Introduction To The Basic Business Intelligence Concepts

datapine

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author.

The Time-Saving Power of Intent Data for Sales

By using the power of intent data, capturing buyer interest has become more feasible for sales. Not only that, but using it will save immense time during your workflow; a win-win on all fronts.

How to compare multiple data streams: actual sales v budget v stretch budget

Phocas

Comparison of sales information against targets has many benefits such as allowing individuals to be more strategic, more motivated and more in control of their actions.

Sales 188

Exclusive Q&A with Phillipa Cameron, CCO of Stuff NZ

Corinium

Ahead of the Chief Customer Officer New Zealand conference, we caught up with Phillipa Cameron, Chief Customer Officer at Stuff NZ to discuss the biggest challenges she faces in her role, and how to tackle them, how she has encouraged Stuff NZ to be more collaborative as well as how a shift to be more customer focused has impacted the organisation.

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Real-time entity resolution made accessible

O'Reilly on Data

The O’Reilly Data Show Podcast: Jeff Jonas on the evolution of entity resolution technologies. In this episode of the Data Show , I spoke with Jeff Jonas , CEO, founder and chief scientist of Senzing , a startup focused on making real-time entity resolution technologies broadly accessible.

A Beginner’s Guide to Tidyverse – The Most Powerful Collection of R Packages for Data Science

Analytics Vidhya

Introduction Data scientists spend close to 70% (if not more) of their time cleaning, massaging and preparing data. That’s no secret – multiple surveys. The post A Beginner’s Guide to Tidyverse – The Most Powerful Collection of R Packages for Data Science appeared first on Analytics Vidhya. Data Science Data Visualization R data cleaning data preprocessing data science data visualization ggplot r packages tidy tidyverse

How ZoomInfo Enhances Your Database Management Strategy

Forward-thinking marketing organizations have continuously invested in a database strategy for enabling marketing processes. Download this ebook to learn how to maintain a strategy that includes refreshed information, database cleanses, and an accurate analysis at the same time.

Seen and Be Seen: How Facial Recognition Will Change Society

DataFloq

With the number of cameras drastically increasing in our world, facial recognition is rapidly taking flight. Facial recognition is a biometric faceprint, where artificial intelligence maps an individual’s face mathematically. This faceprint is then stored in data.

Common Business Intelligence Challenges Facing Entrepreneurs

datapine

“BI is about providing the right data at the right time to the right people so that they can take the right decisions” – Nic Smith. Data analytics isn’t just for the Big Guys anymore; it’s accessible to ventures, organizations, and businesses of all shapes, sizes, and sectors.

Phocas’ product roadmap a hit at PUG.live

Phocas

Market basket analysis, cloud sync and grid visualizations are some of Phocas’ product roadmap highlights. ERP - SAP Business One Events and Trade Shows ERP - Pronto Product

Facebook Insight - Connecting your Data Science & Marketing Teams

Corinium

Over it's lifetime Facebook has become possibly the biggest B2C/B2B marketing channel available to marketers. The platform is a mass generator of big customer data that holds immense potential value for making smarter marketing decisions.

How ZoomInfo Enhances Your ABM Strategy

For marketing teams to develop a successful account-based marketing strategy, they need to ensure good data is housed within its Customer Relationship Management (CRM) software. More specifically, updated data can help organizations outline key accounts for their campaigns. And to begin the targeting process, marketing teams must develop an Ideal Customer Profile (ICP) with appropriate firmographic and behavioral data to ensure they’re going after the correct audience.Download this eBook to learn how to start improving your marketing team's data!

Highlights from the Strata Data Conference in London 2019

O'Reilly on Data

Watch highlights from expert talks covering machine learning, predictive analytics, data regulation, and more. People from across the data world are coming together in London for the Strata Data Conference. Below you'll find links to highlights from the event. Making the future.

Extracting and Analyzing 1000 Basketball Games using Pandas and Chartify

Analytics Vidhya

Introduction I love descriptive statistics. Visualizing data and analyzing trends is one of the most exciting aspects of any data science project. But what. The post Extracting and Analyzing 1000 Basketball Games using Pandas and Chartify appeared first on Analytics Vidhya. Machine Learning Python machine learning python web scraping

Machine Learning Will Be the Next Big Thing in Supply Chain Management

DataFloq

Supply chain management, or SCM, is becoming a more critical job every year, as more consumers turn to e-commerce and warehouses and distribution centers grow. Technology is catching up to the exponential expansion of this industry, but it's been a slow process.

How Restaurant Analytics Can Make Your Business More Profitable

datapine

The restaurant industry is one of the most competitive sectors on the planet. Not only do we as a species need to eat and drink to survive; communal dining is an experience that people have cherished for centuries.

Design Thinking for Product Teams: Leverage Human Insight Throughout Development

Product teams must increase their exposure hours with customers—seeing and hearing them. Human insights and the design thinking framework can be applied to your development cycle to help you build better products and experiences for your customers.