IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 78

Data Science Data Analytics Prescriptive Analytics Analytics 78

datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

O'Reilly on Data

DECEMBER 12, 2019

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML.

Machine Learning 187

Machine Learning Modeling Testing Risk Management 187

CIO Business Intelligence

JUNE 14, 2023

Certification of Professional Achievement in Data Sciences The Certification of Professional Achievement in Data Sciences is a nondegree program intended to develop facility with foundational data science skills. The online program includes an additional nonrefundable technology fee of US$395 per course.

Big Data 124

Big Data Data Analytics Analytics Predictive Modeling 124

Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. Data Science — A Venn Diagram of Skills. Data science encapsulates both old and new, traditional and cutting-edge. 3 Components of Data Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Data Science 101

JUNE 10, 2019

Getting your first data science job might be challenging, but it’s possible to achieve this goal with the right resources. Before jumping into a data science career , there are a few questions you should be able to answer: How do you break into the profession? What skills do you need to become a data scientist?

Data Science 96

Data Science Statistics Predictive Modeling Machine Learning 96

Smarten

JANUARY 24, 2019

What is Automated Machine Learning? Quite simply, it is the means by which your business can optimize resources, encourage collaboration and rapidly and dependably distribute data across the enterprise and use that data to predict, plan and achieve revenue goals.

Machine Learning 40

Machine Learning Predictive Modeling Predictive Analytics Forecasting 40

Smarten

APRIL 25, 2024

Whether you are trying to solve a business problem, get to the heart of that problem, find a business opportunity, predict the need for resources, new products or locations or understanding changes in your customer buying behavior, you don’t have time to learn complex tools or take training in analytics.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

CIO Business Intelligence

JUNE 7, 2022

Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. In business, predictive analytics uses machine learning, business rules, and algorithms.

Data Analytics 129

Data Analytics Diagnostic Analytics Management Analytics 129

Domino Data Lab

JULY 9, 2019

Chris Wiggins , Chief Data Scientist at The New York Times, presented “Data Science at the New York Times” at Rev. Wiggins also indicated that data science, data engineering, and data analysis are different groups at The New York Times. Session Summary. Transcript. Feel free to email me.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Smarten

MARCH 18, 2019

Data Science and Predictive Analytics Made Simple! Imagine a world where data science and predictive analytics tools are created for business users!

Predictive Analytics 40

Predictive Analytics Visualization Software Analytics 40

Smarten

MARCH 5, 2024

The Citizen Data Scientist phenomenon is in full swing and, while the approach has its detractors, the proof is in success, and many organizations are actively succeeding using the Citizen Data Scientist approach.

Predictive Modeling 62

Predictive Modeling Consulting Machine Learning Visualization 62

Cloudera

JULY 18, 2018

To arrive at quality data, organizations are spending significant levels of effort on data integration, visualization, and deployment activities. Additionally, organizations are increasingly restrained due to budgetary constraints and having limited data sciences resources.

Machine Learning 51

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 51

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 121

Predictive Analytics Analytics Predictive Modeling Data mining 121

DataRobot

NOVEMBER 1, 2021

Practitioners in the AI space are focused on the speed and accuracy of model predictions. But the end game for the applicability of models is not in the predictions, but the decisions they enable, and predictive models alone don’t ensure better decisions. What Is Decision Intelligence?

Machine Learning 98

Machine Learning Manufacturing Predictive Modeling Optimization 98

CIO Business Intelligence

OCTOBER 13, 2023

Data scientist As companies embrace gen AI, they need data scientists to help drive better insights from customer and business data using analytics and AI. For most companies, AI systems rely on large datasets, which require the expertise of data scientists to navigate.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 2) Data Discovery/Visualization. We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Access to Flexible, Intuitive Predictive Modeling. Apply Data Filters. Forecasting. Classification.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

Smarten

FEBRUARY 28, 2019

If Data Science was once the sole domain of analysts and data scientists, Augmented Data Science represents the democratized view of this domain. Augmented data science automates and simplifies analysis with machine learning so implementation, training and adoption of these tools is rapid and successful.

Data Science 40

Data Science IT Machine Learning Predictive Modeling 40

Smarten

OCTOBER 31, 2022

Auto Insights and toolsets that leverage machine learning. Embedded BI with integration APIs allows users to leverage single sign-on within familiar software and perform analytics from within that solution. Key Influencer Analysis. Clickless Analytics with Natural Language Processing (NLP) and easy ‘Google-type’ searches and queries.

Key Performance Indicator 67

Key Performance Indicator Analytics Cost-Benefit Predictive Modeling 67

CIO Business Intelligence

MAY 9, 2024

That means having a deep understanding of various AI technologies, including machine learning, natural language processing, retrieval-augmented generation (RAG), and, where applicable, robotics, Mathison says. This includes skills in statistical analysis, data visualization, and predictive modeling.

Risk Management 134

Risk Management Risk Cost-Benefit Technology 134

Sisense

APRIL 10, 2020

One of the most-asked questions from aspiring data scientists is: “What is the best language for data science? People looking into data science languages are usually confused about which language they should learn first: R or Python. NLP can be used on written text or speech data. R or Python?”.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. The Importance of Exploratory Analytics in the Data Science Lifecycle. imputation of missing values). ref: [link].

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. 42% of data scientists are solo practitioners or on teams of five or fewer people. 42% of data scientists are solo practitioners or on teams of five or fewer people. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

Smarten

DECEMBER 3, 2023

‘Augmented analytics is the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation and insight explanation to augment how people explore and analyze data in analytics and BI platforms. What is self-service analytics? We should probably explain before we move on.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. For example, streaming data from sensors to an analytics platform where it is processed and visualized immediately.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

DataRobot

JANUARY 13, 2022

But they often don’t have enough data scientists with the full range of domain expertise to realize its full value. Data scientists typically come equipped with skills in three key areas: mathematics and statistics, data science methods, and domain expertise. DataRobot is just such a platform.

ROI 52

ROI Machine Learning Experimentation Data Science 52

Smarten

MARCH 13, 2024

For a number of years, Gartner and other technology research and analysis firms have predicted and monitored the growth of this phenomenon. In fact, Gartner predicted that, ‘…40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’

Analytics 52

Analytics Predictive Modeling Strategy Enterprise 52

Smarten

AUGUST 21, 2019

These tools allow business users to leverage augmented analytics that provide guides and suggestions to help the business user more quickly and effectively produce clear advanced analytics with little to no training, thereby transforming the average business user into a Citizen Data Scientist.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

datapine

DECEMBER 4, 2019

Moreover, as most predictive analytics capabilities available today are in their infancy — they have simply not been used for long enough by enough companies on enough sources of data – so the material to build predictive models on was quite scarce. Last but not least, there is the human factor again.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

FineReport

MARCH 31, 2024

In 2024, business intelligence (BI) software has undergone significant advancements, revolutionizing data management and decision-making processes. Harnessing the power of advanced APIs, automation, and AI, these tools simplify data compilation, organization, and visualization, empowering users to extract actionable insights effortlessly.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Domino Data Lab

SEPTEMBER 18, 2019

This post covers data exploration using machine learning and interactive plotting. Models are at the heart of data science. Data exploration is vital to model development and is particularly important at the start of any data science project. Introduction. fit(scaled_df).:

Visualization 99

Visualization Interactive Machine Learning Data Science 99

Smarten

FEBRUARY 17, 2022

Without understanding the shift in workflow, responsibilities and how the use of data will change the enterprise, it is unlikely that the business will succeed in its Citizen Data Scientist initiative.

Predictive Modeling 76

Predictive Modeling Digital Transformation Enterprise Data Science 76

Birst BI

AUGUST 23, 2018

A key goal of AI or machine learning automation is to have machines complete tasks for you, freeing up time so you can focus on the more complex, higher-value tasks. However, there are simply not enough data scientists in the world to deliver on the AI potential. The Outsourcing of Data Science Functions.

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Domino Data Lab

AUGUST 12, 2021

For data, this refinement includes doing some cleaning and manipulations that provide a better understanding of the information that we are dealing with. In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

Smarten

SEPTEMBER 17, 2019

This augmented analytics solution includes smart data visualization, assisted predictive modeling and a self-serve data preparation assisted by machine learning to help business users without any data science skills to create, use and share predictive models on their own.

Analytics 51

Analytics Predictive Modeling Reporting Machine Learning 51

datapine

JANUARY 31, 2022

BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions. BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. 6) Smart and faster reporting.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214