The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. It also owns Google’s internal time series forecasting platform described in an earlier blog post. Our team does a lot of forecasting. Our team does a lot of forecasting.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

IBM Big Data Hub

NOVEMBER 29, 2023

But Downer envisioned a partnership that would allow them to delve deeper into the data, unearthing more insights that could add value to operations. They combined forces with the experts at IBM to reach toward the expanding horizons of data science. Downer was able to streamline modeling times with watsonx.ai

Predictive Modeling 69

Predictive Modeling Data-driven Data Science Forecasting 69

Smarten

NOVEMBER 23, 2023

“These tools enable data literacy and digital transformation and increase team productivity and creativity, encouraging power users and those with average technology skills to dive into analytics ad use fact-based decision-making to improve market positioning.”

Publishing 62

Publishing Marketing Analytics Predictive Modeling 62

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

IBM Big Data Hub

MAY 18, 2023

IBM Automation Decision Services is designed to enable organizations to combine prescriptive business rules with predictive models to help them make more informed operational decisions to improve customer experience and make organizations run more effectively.

Reporting 93

Reporting Scorecard Predictive Modeling Machine Learning 93

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. Forecasting. Classification. Hypothesis Testing. Correlation.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

Smarten

MAY 29, 2023

World-renowned technology analysis firm Gartner defines the role this way, ‘A citizen data scientist is a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics. ‘If Advanced data preparation.

Prescriptive Analytics 52

Prescriptive Analytics Predictive Modeling Digital Transformation Business Objectives 52

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 Predictive Modeling 106

Cloudera

MARCH 21, 2022

Data Science tools, algorithms, and practices are rapidly evolving to solve business problems on an unprecedented scale. This makes data science one of the most exciting fields to be in. There are well-known barriers that slow down predictive modeling or application development.

Machine Learning 80

Machine Learning Predictive Modeling Data Science Testing 80

Cloudera

OCTOBER 14, 2020

By combining profound airline operation expertise, data science, and engine analytics to a predictive maintenance schedule, Lufthansa Technik can now ensure critical parts are on the ground (OTG) when needed, instead of the entire aircraft being OTG and not producing revenue.

Machine Learning 97

Machine Learning Modeling Cost-Benefit Testing 97

Smarten

JANUARY 27, 2023

Smarten has announced the launch of Predictive Model Mark-Up Language (PMML) Integration capability for its Smarten Augmented Analytics suite of products. Simply create the predictive model, using your favorite platform, export the model as a PMML file and import that model to Smarten.

Predictive Modeling 52

Predictive Modeling Analytics Predictive Analytics Business Intelligence 52

Cloudera

APRIL 11, 2023

As the entire Cloudera Data Platform is built on open source projects, we find it crucial to participate in and contribute back to the community. Applied ML Prototypes (AMPs) are fully built end-to-end data science solutions that allow data scientists to go from an idea to a fully working machine learning model in a fraction of the time.

Forecasting 72

Forecasting Machine Learning Recreation/Entertainment Sales 72

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

APRIL 25, 2024

Artificial Intelligence (AI) and Machine Learning (ML) elements support Citizen Data Scientists and help users prepare data, achieve automated data insights and create, share and use predictive models.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

O'Reilly on Data

MARCH 24, 2020

Why is high-quality and accessible data foundational? The assumed value of data is a myth leading to inflated valuations of start-ups capturing said data. Generating data with a pre-specified analysis plan and running that analysis is good. Re-analyzing existing data is often very bad.”

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346

Insight

MARCH 18, 2019

Bias in Machine Learning Algorithms (Bottom Photos Source: ProPublica ; Top Photos Source: Pexels.com) Biases in predictive modeling are a widespread issue Machine learning and AI applications are used across industries, from recommendation engines to self-driving cars and more. 5 is labeled as low.

Machine Learning 77

Machine Learning Predictive Modeling Modeling Metrics 77

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. If an attacker can receive many predictions from your model API or other endpoint (website, app, etc.),

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

Smarten

OCTOBER 31, 2022

Embedded BI with integration APIs allows users to leverage single sign-on within familiar software and perform analytics from within that solution.

Key Performance Indicator 67

Key Performance Indicator Analytics Cost-Benefit Predictive Modeling 67

datapine

NOVEMBER 27, 2019

Hotels try to predict the number of guests they can expect on any given night in order to adjust prices to maximize occupancy and increase revenue. There are plenty of big data examples used in real life, shaping our world, be it in the buying experience or managing customers’ data. And it’s completely free!

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

DECEMBER 3, 2023

Look for a full suite of products and modules, including self-serve data preparation , assisted predictive modeling , smart data visualization , and a product that is built on a natural language processing (NLP) foundation for easy NLP searching.

Analytics 40

Analytics Predictive Modeling Cost-Benefit Visualization 40

DataRobot Blog

JUNE 23, 2022

Most successful ML and AI projects are replacing an existing prediction with a more accurate and/or faster one. Human intuition is relied on, or an older, hand-build BI/predictive model exists, or perhaps a set of heuristics were documented that more or less predict something. Case Study.

Predictive Modeling 59

Predictive Modeling Modeling Data Science Measurement 59

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

Sisense

APRIL 10, 2020

In Talking Data , we delve into the rapidly evolving worlds of Natural Language Processing and Generation. Text data is proliferating at a staggering rate, and only advanced coding languages like Python and R will be able to pull insights out of these datasets at scale. NLP can be used on written text or speech data.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Smarten

APRIL 12, 2023

About Smarten The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Snapshot 52

Snapshot Key Performance Indicator KPI Business Intelligence 52

Sisense

SEPTEMBER 9, 2019

We were most interested in exploring if it was possible to predict the return rate on a new product based on historical return rates of products with similar features. Then we ran Kraken’s machine learning and predictive modeling engine to get the results. It will be iterative.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Forecasting Data-driven 75

DataRobot Blog

JANUARY 27, 2019

In my previous articles Predictive Model Data Prep: An Art and Science and Data Prep Essentials for Automated Machine Learning, I shared foundational data preparation tips to help you successfully. by Jen Underwood. Read More.

Machine Learning 92

Machine Learning Modeling Predictive Modeling Predictive Analytics 92

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: optimizing healthcare processes to save lives, data analysis for emergency resource management, building smarter cities with data science, using data and analytics to fight climate change, tackle the food crisis or prioritize actions against poverty, and more.

Digital Transformation 67

Digital Transformation Machine Learning Optimization Data Lake 67

Cloudera

APRIL 13, 2021

But while the company is united by purpose, there was a time when its teams were kept apart by a data platform that lacked the scalability and flexibility needed for collaboration and efficiency. Disparate data silos made real-time streaming analytics, data science, and predictive modeling nearly impossible.

Enterprise 75

Enterprise Cost-Benefit Data Warehouse Data Architecture 75

Cloudera

NOVEMBER 18, 2020

To ensure maximum momentum and flawless service the Experian BIS Data Enrichment team decided to use the power of big data by utilizing Cloudera’s Data Science Workbench. The pipeline provides its clinicians fast access to real-time patient data and prediction models.

Internet Publishing and Broadcasting 120

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 120

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

Domino Data Lab

OCTOBER 7, 2020

In this blog we show what the changes in behavior of data are in high dimensions. In our next blog we discuss how we try to avoid these problems in applied data analysis of high dimensional data. Data Has Properties. Statistics developed in the last century are based on probability models (distributions).

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

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

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

IBM Big Data Hub

OCTOBER 16, 2023

Foundation models can use language, vision and more to affect the real world. GPT-3, OpenAI’s language prediction model that can process and generate human-like text, is an example of a foundation model. Enable responsible, transparent and explainable data and AI workflows with watsonx.governance.

Risk 76

Risk Modeling Management Metadata 76

Juice Analytics

MARCH 11, 2021

How are you going to turn that data into a solution? There are many paths to consider: Visual representations that reveal patterns in the data and make it more human readable. Predictive models to take descriptive data and attempt to tell the future. In particular, data products require more C.L.I.C.

Predictive Modeling 128

Predictive Modeling Visualization Reporting Interactive 128

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

datapine

JANUARY 31, 2022

Although the oil company has been producing massive amounts of data for a long time, with the rise of new cloud-based technologies and data becoming more and more relevant in business contexts, they needed a way to manage their information at an enterprise level and keep up with the new skills in the data industry.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214