DataKitchen

JANUARY 5, 2021

Remote working has revealed the inconsistency and fragility of workflow processes in many data organizations. The data teams share a common objective; to create analytics for the (internal or external) customer. Data Science Workflow – Kubeflow, Python, R. Data Engineering Workflow – Airflow, ETL.

Testing 147

Testing Data Governance Metadata Visualization 147

CIO Business Intelligence

JUNE 7, 2022

But the success of their AI initiatives depends on more than just data and technology — it’s also about having the right people on board. An effective enterprise AI team is a diverse group that encompasses far more than a handful of data scientists and engineers. Data scientist. ML engineer.

Machine Learning 145

Machine Learning Data Science Consulting Metrics 145

CIO Business Intelligence

JUNE 28, 2022

Some call data the new oil. Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

Management 132

Management Internet of Things Statistics Data-driven 132

CIO Business Intelligence

MARCH 1, 2023

of Huawei employees are engaged in Research and Development (R&D), which over the last decade has been supported with US$132.5 Six distribution product R&D teams have been set up and more than 200 new products and solutions will be released to the SME market this year. Moreover, 54.8% billion investment.

Marketing 91

Marketing Enterprise Digital Transformation Sales 91

CIO Business Intelligence

NOVEMBER 9, 2023

Foundry / AI Priorities Study 2023 The ideal individual to assume this role should have much more than top technology and AI skills, says Colin Reeves, principal data and AI recruiter at ConSol Partners in Los Angeles. They should be a champion for smart AI adoption, and be able to recognize and balance AI benefits with risks.

IT 120

IT Strategy Reporting Visualization 120

DataKitchen

AUGUST 27, 2021

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

datapine

MARCH 31, 2022

Does data excite, inspire, or even amaze you? Despite these findings, the undeniable value of intelligence for business, and the incredible demand for BI skills, there is a severe shortage of BI-based data professionals – with a shortfall of 1.5 2) Top 10 Necessary BI Skills. 3) What Are the First Steps To Getting Started?

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

DataKitchen

MAY 10, 2021

Data errors impact decision-making. Data errors infringe on work-life balance. Data errors also affect careers. If you have been in the data profession for any length of time, you probably know what it means to face a mob of stakeholders who are angry about inaccurate or late analytics.

Testing 214

Testing Manufacturing Data Quality Statistics 214

CIO Business Intelligence

JUNE 1, 2022

The company is applying winning insights from rapid, data-driven, evolutionary models versus relying on engine speed and aerodynamics alone to win races. For businesses like the McLaren Group, these two trends are at the core of the conglomerate’s digital transformation and competitive strategy, on and off the track. .

Manufacturing 98

Manufacturing Digital Transformation Predictive Analytics Strategy 98

Sisense

MAY 27, 2019

That means there’s one Hell of a lot of data running through your organization. So, given the choice, which analytics job title should you choose: A data engineer or a data scientist? Digging Deep For Data Diamonds – The Data Engineer. Data’s like diamonds. That’s the job of the data engineer.

Statistics 75

Statistics Machine Learning Visualization Big Data 75

AWS Big Data

MAY 4, 2023

Welcome to the era of data. The sheer volume of data captured daily continues to grow, calling for platforms and solutions to evolve. The Amazon Sustainability Data Initiative (ASDI) uses the capabilities of Amazon S3 to provide a no-cost solution for you to store and share climate science workloads across the globe.

Data Processing 92

Data Processing Metadata Informatics Interactive 92

Domino Data Lab

JULY 28, 2021

The data science lifecycle (DLSC) has been defined as an iterative process that leads from problem formulation to exploration, algorithmic analysis and data cleaning to obtaining a verifiable solution that can be used for decision making. The data science process in a business environment begins with the Manage stage.

Data Science 59

Data Science Enterprise Modeling Experimentation 59

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity.

Testing 307

Testing Machine Learning Consulting Data Quality 307

DataRobot

JUNE 23, 2021

As they strive to improve models, data scientists continually try new approaches to refine their predictions. To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. In data science , the best results come through experimentation. So let’s dig in! Run AutoPilot.

Machine Learning 52

Machine Learning Modeling Experimentation Visualization 52

Cloudera

JANUARY 30, 2019

It’s official – Cloudera and Hortonworks have merged , and today I’m excited to announce the availability of Cloudera Data Science Workbench (CDSW) for Hortonworks Data Platform (HDP). Trusted by large data science teams across hundreds of enterprises —. Sound familiar? What is CDSW? Install any library or framework (e.g.

Data Science 72

Data Science Machine Learning Experimentation Cost-Benefit 72

CIO Business Intelligence

MARCH 16, 2022

The pace of technology has evolved so rapidly over the last few years, multiplied by the pandemic, that it’s hard to keep track — and what’s most in demand today may be obsolete tomorrow. Kiran Marri, chief scientist at CSS Corp., Identifying which emerging technologies will prove most useful is a challenge, though.

Forecasting 92

Forecasting Machine Learning Technology Enterprise 92

Domino Data Lab

JUNE 26, 2019

Even the most sophisticated data science organizations struggle to keep track of their data science projects. But while there are a legion of tools for individual data scientists, the needs of data science leaders have not been well-served. They need help tracking projects.

Data Science 65

Data Science Dashboards Metadata Snapshot 65

IBM Big Data Hub

AUGUST 11, 2023

The advancement of computing power over recent decades has led to an explosion of digital data, from traffic cameras monitoring commuter habits to smart refrigerators revealing how and when the average family eats. Both computer scientists and business leaders have taken note of the potential of the data.

Data Science 56

Data Science Machine Learning Cost-Benefit Deep Learning 56

Depict Data Studio

JULY 13, 2021

— Thank you to Ann Emery, Depict Data Studio, and her Simple Spreadsheets class for inviting us to talk to them about the use of statistics in nonprofit program evaluation! And we’ve never met a nonprofit so flush that they had money to track people they don’t serve. . & Alison Nagel, Ph.D 6 Months to 40 Years).

Statistics 98

Statistics Testing Recreation/Entertainment Experimentation 98

The Unofficial Google Data Science Blog

NOVEMBER 19, 2015

We will continue to bring you posts from the range of data science activities at Google. We briefly highlight some of the things we look for in data scientists we hire at Google and give tips on ways to prepare. At Google we’re always looking for talented people, and we’re interested in hiring great data scientists.

Statistics 75

Statistics Data Science Machine Learning Sales 75

Sisense

JANUARY 15, 2021

In Building Bridges , we focus on helping end users, app builders, and data experts select and roll out analytics platforms easily and efficiently. We live in a world driven by data. As we have previously posted, the BI group is often the department that approaches the data teams for access to an analytics solution.

Analytics 75

Analytics Data-driven Business Intelligence Visualization 75

Domino Data Lab

JUNE 10, 2020

Today, we announced the latest release of Domino’s data science platform which represents a big step forward for enterprise data science teams. You can identify data drift, missing information, and other issues, and take corrective action before bigger problems occur. Github, Bitbucket, Gitlab).

Data Science 82

Data Science Enterprise Experimentation Modeling 82

Cloudera

MAY 22, 2018

Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. As data scientists iteratively develop models, they often experiment with datasets, features, libraries, and algorithms as well as tuning hyperparameters.

Data Science 41

Data Science Snapshot Machine Learning Metadata 41

Domino Data Lab

AUGUST 6, 2021

Data science is an incredibly complex field. Framing data science projects within the four steps of the data science lifecycle (DSLC) makes it much easier to manage limited resources and control timelines, while ensuring projects meet or exceed the business requirements they were designed for. 4 Steps in the DSLC.

Data Science 75

Data Science Testing Modeling Publishing 75

Jen Stirrup

MAY 5, 2020

Recently, I gave a Make Your Data Work Monday webinar on the complexities of the data sources for data science in Azure, and I thought it important enough to turn into an actual post. How can you differentiate the different opportunities to store your data in Azure? Organizations need to recast storing their data.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

Domino Data Lab

JUNE 15, 2021

These companies often undertake large data science efforts in order to shift from “data-driven” to “model-driven” operations, and to provide model-underpinned insights to the business. The typical data science journey for a company starts with a small team that is tasked with a handful of specific problems.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

Domino Data Lab

JUNE 23, 2019

Skomoroch advocates that organizations consider installing product leaders with data expertise and ML-oriented intuition (i.e., Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. It is similar to R&D.

Management 110

Management Machine Learning Experimentation Metrics 110

Depict Data Studio

MAY 8, 2023

All of these classes fall under the broad data communications umbrella. One class focuses on data analysis (cleaning and tabulating our raw datasets to get them ready for graphs). Class 1: Simple Spreadsheets: How to Analyze Data from Start to Finish in Excel Need to make sense of spreadsheets? Not sure where to start?

Dashboards 52

Dashboards Visualization Reporting Interactive 52

Sisense

JUNE 6, 2019

But frankly, as a data geek, it is a pretty boring report. As a data geek, I want to know exactly why we performed so well! Published a few months after the MQ, this report provides more than a glimpse at the mountain of data behind the Gartner MQ. At Sisense, we make sure data teams have the best tools to ingest, clean, and.

Reporting 75

Reporting Business Intelligence Visualization Digital Transformation 75

Data Science 101

MAY 6, 2019

At Springboard , we recently sat down with Michael Beaumier, a data scientist at Google, to discuss his transition into the field, what the interview process is like, the future of data wrangling, and the advice he has for aspiring data professionals. in physics and now you’re a data scientist.

Data Science 98

Data Science Modeling Machine Learning Testing 98

Jet Global

JULY 2, 2019

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.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Domino Data Lab

MARCH 27, 2019

Special thanks to Addison-Wesley Professional for permission to excerpt the following “Manipulating data with dplyr” chapter from the book, Programming Skills for Data Science: Start Writing Code to Wrangle, Analyze, and Visualize Data with R. Data scientists spend countless hours wrangling data.

Statistics 85

Statistics Data Science Visualization IT 85

bridgei2i

JANUARY 25, 2022

The Basic Guide to Data Science at the Workplace. The Basic Guide to Data Science at the Workplace. In this podcast episode, AI enthusiasts Anirudh and Janci talk about how sincere curiosity and passion for learning can help anyone understand data science and become an active contributor. And now you’re a data scientist.

Data Science 52

Data Science Machine Learning Data-driven Statistics 52

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. Types of Modeling Tools.

Modeling 64

Modeling IT Risk Management Deep Learning 64

Cloudera

NOVEMBER 16, 2017

Cloudera Data Science Workbench (CDSW) is a self-service collaboration platform for data scientists. It offers: Secure access to Cloudera data. Support for Python, R, and Scala. for the Oracle Big Data Appliance.) Read this article on deep learning with Apache MXNet on Cloudera Data Science Workbench.

Data Science 40

Data Science Deep Learning Big Data Software 40

Insight

MARCH 29, 2019

Over the last three years, I’ve worked with more than 500 Insight Fellows , coaching them as they transition to thriving industry careers in data science, data engineering, and artificial intelligence. To get some answers, Insight’s NYC office hosted a discussion focused on the many paths of growth available to today’s data scientists.

Data Science 73

Data Science Management ROI Data Processing 73