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 94

Marketing Enterprise Digital Transformation Sales 94

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 126

IT Strategy Reporting Visualization 126

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

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 108

Manufacturing Digital Transformation Predictive Analytics Strategy 108

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 90

Data Processing Metadata Informatics Interactive 90

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 71

Data Science Machine Learning Experimentation Cost-Benefit 71

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 95

Forecasting Machine Learning Technology Enterprise 95

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

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

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

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

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

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

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

DataKitchen

AUGUST 13, 2021

If a company can use data to identify compounds more quickly and accelerate the development process, it can monetize its drug pipeline more effectively. DataOps automation provides a way to boost innovation and improve collaboration related to data in pharmaceutical research and development (R&D).

Testing 246

Testing Dashboards Marketing Measurement 246

O'Reilly on Data

FEBRUARY 11, 2020

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

Domino Data Lab

JULY 15, 2021

In the multiverse of data science, the tool options continue to expand and evolve. While there are certainly engineers and scientists who may be entrenched in one camp or another (the R camp vs. Python, for example, or SAS vs. MATLAB), there has been a growing trend towards dispersion of data science tools. Snowflake ).

Data Science 145

Data Science Visualization Modeling Enterprise 145

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

OCTOBER 19, 2023

Power BI is Microsoft’s interactive data visualization and analytics tool for business intelligence (BI). With Power BI, you can pull data from almost any data source and create dashboards that track the metrics you care about the most. Explore ‘What-ifs’ Like Excel, Power BI offers slicers for comparing scenarios.

Slice and Dice 123

Slice and Dice Scorecard Metrics Visualization 123

Timo Elliott

JANUARY 18, 2021

And so we scrambled the crisis management team and started looking at the data from very, very early on. And we have our Qualtrics software for customer employee experience, and we have used that to keep track of the pulse of our employees to make sure that everybody is coping as well as they can with the pandemic.

IT 71

IT Dashboards Digital Transformation Data-driven 71

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

The Unofficial Google Data Science Blog

DECEMBER 4, 2015

by AARON BECKER In a previous post, we described how data scientists at Google used Sawzall to perform powerful, scalable analysis. As such, it’s great for writing quick one-off analysis code and iterating on it as we come to a better understanding of the data. a user’s IP address) and which ones are innocuous (e.g.

Statistics 54

Statistics Interactive Software Modeling 54

DataRobot Blog

JANUARY 10, 2023

ML model builders spend a ton of time running multiple experiments in a data science notebook environment before moving the well-tested and robust models from those experiments to a secure, production-grade environment for general consumption. 42% of data scientists are solo practitioners or on teams of five or fewer people.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

Cloudera

AUGUST 25, 2020

Introducing Model Monitoring & Metrics Store In Cloudera Data Science Workbench. With only about 35% of machine learning models making into production in the enterprise ( IDC ), it’s no wonder that production machine learning has become one of the most important focus areas for data scientists and ML engineers alike.

Machine Learning 74

Machine Learning Metrics Modeling Enterprise 74

CIO Business Intelligence

FEBRUARY 15, 2023

Bayer is using drones to collect farming data across 80 million acres and satellite data to predict soil moisture down to the square meter. On the heels of one of the largest cloud transformations in Europe, Sagar has Bayer on track for a highly digital future. Following are excerpts from that conversation.

Digital Transformation 102

Digital Transformation Experimentation Strategy Modeling 102

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

Cloudera

APRIL 13, 2021

In our humble opinion, we believe that’s Cloudera Data Platform (CDP). That’s because CDP has made it possible for them to modernize their legacy data platforms and extend machine learning (ML) and real-time analytics to public cloud, all while gaining cross-functional collaboration across the enterprise. .

Enterprise 73

Enterprise Cost-Benefit Data Warehouse Data Architecture 73

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

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

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