Smart Data Collective

JUNE 26, 2019

There’s a growing number of tools that you can use to analyze data for a business. But you may not be overly confident in the results if you don’t take the data’s blind spots into account. There’s no single way to do that, but we’ll look at some possibilities here. The first thing to keep in mind is that a blind spot generally represents an “unknown unknown.” In other words, it’s a factor you didn’t take into account because you didn’t

ROI 100

ROI Statistics Machine Learning Measurement 100

Analytics Vidhya

JUNE 26, 2019

Overview What does a data scientist do on a day-to-day basis? A popular and must-know question We analyze this question from a data scientist’s. The post Top 5 Must-Read Answers – What does a Data Scientist do on a Daily Basis? appeared first on Analytics Vidhya.

Analytics 300

Analytics Data Science 300

Jedox

JUNE 26, 2019

We are pleased to welcome an expert in Financial Planning and Analysis (FP&A), Mr. Anders Liu-Lindberg, as a guest to the Jedox blog. Mr. Liu-Lindberg is a Senior Finance Business Partner at Maersk and co-author of the book “Create Value as a Finance Business Partner.” He is also a finance industry blogger on LinkedIn with more than 33,000 followers.

Finance 89

Finance Data-driven Forecasting Marketing 89

Analytics Vidhya

JUNE 26, 2019

DataHack Summit 2019 Bringing Together Futurists to Achieve Super Intelligence DataHack Summit 2018 was a grand success with more than 1,000 attendees from various. The post Announcing DataHack Summit 2019 – The Biggest Artificial Intelligence and Machine Learning Conference Yet appeared first on Analytics Vidhya.

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Machine Learning Analytics Deep Learning 229

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

Visualization

Dataiku

JUNE 26, 2019

Last year when we surveyed over one hundred data professionals, they ranked organizational change as their third biggest data challenge (behind data cleaning and model productionalization). However, this year, organizational change moved up to the second place slot, suggesting that organizations have not yet overcome the culture change obstacles to data integration.

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Data Integration Modeling Data Transformation 95

Smart Data Collective

JUNE 26, 2019

The insurance industry is based on the idea of managing risk. To determine this risk, the industry must consult data and see what trends are evident to draft their risk profiles. The journal Risk Management and Insurance Review mentions that historically, in the latter half of the twentieth century, the analysis of trends was the primary driver in determining risk in the insurance business.

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Insurance Data Analytics Analytics IoT 92

Smart Data Collective

JUNE 26, 2019

Medical care has relied on the education and expertise of doctors. Human error is common and 250,000 people per year die from medical errors. As the third-leading cause of death in the United States, limiting errors is a key focus in the healthcare industry. Big data and predictive analytics will lead to healthcare improvement. But how? Health IT Analytics previously published an excellent paper on some of the best use cases of predictive analytics in healthcare.

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Predictive Analytics Analytics Insurance Cost-Benefit 91

IBM Big Data Hub

JUNE 26, 2019

Businesses should consider a database that is both powered by, and built for, AI. Learn why you should start your AI journey with Db2 11.5.

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Enterprise 83

Smart Data Collective

JUNE 26, 2019

Python is arguably the best programming language for machine learning. However, many aspiring machine learning developers don’t know where to start. They should look into the scikit-learn library, which is one of the best for developing machine learning applications. It is free and relatively easy to install and learn. Why machine learning programmers should be familiar with scikit-learn.

Machine Learning 77

Machine Learning Statistics Testing IoT 77

Jedox

JUNE 26, 2019

We are pleased to welcome an expert in Financial Planning and Analysis (FP&A), Mr. Anders Larsen Lie-Lindberg, as a guest to the Jedox blog. Mr. Lindberg is a Senior Finance Business Partner at Maersk and co-author of the book “Create Value as a Finance Business Partner.” He is also a finance industry blogger on LinkedIn with more than 33,000 followers.

Finance 40

Finance Data-driven Forecasting Marketing 40

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

Management

Data Virtualization

JUNE 26, 2019

In all of my conversations about data, the same words and phrases keep coming up – agility, performance, security, governance, the heterogeneity of data sources (data silos), and ease of access, just to name a few. I use them so.

Data Governance 40

Data Governance Big Data 40

Nutanix

JUNE 26, 2019

We are excited to be a sponsor of the HR Leadership Summit in San Diego, July 28, 2019 - July 30, 2019. The HR Leadership Summit is a gathering of C-Suite Executives and senior decision makers from Fortune 1000 and leading enterprise organizations.

Enterprise 20

Enterprise 20

Domino Data Lab

JUNE 26, 2019

Even the most sophisticated data science organizations struggle to keep track of their data science projects. Data science leaders want to know, at any given moment, not just how many data science projects are in flight but what the latest updates and roadblocks are when it comes to model development and what projects need their immediate attention. .

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Data Science Dashboards Metadata Snapshot 65

CDW Research Hub

JUNE 26, 2019

For the third year in a row, Sirius has been ranked the world’s top managed services provider (MSP) in Channel Futures/Channel Partners’ 2019 MSP 501 , which is widely viewed as the most comprehensive global survey of MSPs. “Every year, we have hundreds more applications than the year before. That means that every year, the competition gets more and more fierce,” said Kris Blackmon, senior editor of Channel Futures / Channel Partners and program lead for the MSP 501.

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Management IT 73

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.

Experimentation

Sisense

JUNE 26, 2019

Data engineers are considered the real builders in the data world today, and one of the main reasons is that they help organizations get value out of their data. For an enterprise company , that can mean building and maintaining data pipelines or optimizing database queries and anything in between. If you are a data engineer, then you know that data is your most valuable asset.

Enterprise 75

Enterprise Data Warehouse Dashboards Modeling 75