DataKitchen

MAY 10, 2021

They cause people to work long hours at the expense of personal and family time. 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. Data sources must deliver error-free data on time.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Cloudera

NOVEMBER 3, 2021

One of the best ways to make a substantial improvement in processing time is to, if you haven’t already, switched from CPUs to GPUs. Time required to configure an environment with GPUs. Time required to configure an environment with GPUs. Time required to refactor CPU code. Photo Credit: Kaggle. Checkmate reason 2.

Deep Learning 117

Deep Learning Machine Learning Data Science Cost-Benefit 117

The Data Visualisation Catalogue

JANUARY 21, 2024

This chart was originally used as a trading tool to visualise and analyse the price movements over time. Example Georgios Karamanis adapted this visualisation method for another purpose: to visualise the viewership of the TV series The Great British Bake Off. Each symbol or ‘anchor’ represents a trading session.

Snapshot 77

Snapshot Publishing Visualization 77

Sisense

JULY 28, 2019

The case of business data takes us all the way back to the ‘70s and the introduction of databases, which at the time were very expensive and extremely limited in functionality. For basic reporting, you don’t need fancier technology or languages than SQL, you can rely on that language all the time. SQL vs. Python and R.

Statistics 75

Statistics Machine Learning Business Intelligence Measurement 75

DataRobot Blog

JULY 28, 2022

Companies are emphasizing the accuracy of machine learning models while at the same time focusing on cost reduction, both of which are important. In this blog post, we would like to present some examples of actual cases in which noise reduction had a significant effect in real-world applications, and in which powerful features were obtained.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

The Data Visualisation Catalogue

JANUARY 24, 2023

After consuming a number of YouTube videos, blog posts, articles, and playing around with ChatGPT, I felt the need to write down my thoughts and observations on the topic. This is probably due to this tool demonstrating the potential to revolutionise the way we search and interact with information over the internet.

Visualization 113

Visualization Interactive Data-driven Testing 113

Alation

NOVEMBER 2, 2022

Alation has raised $123M in Series E funding at a valuation of in excess of $1.7B, a material increase from the Series D round in June of last year, particularly in the context of the recent stock-market decline. This quarter has been a uniquely challenging time to raise capital. The timing may surprise some.

Data Governance 98

Data Governance Marketing Finance Data Lake 98

The Unofficial Google Data Science Blog

APRIL 17, 2017

by ERIC TASSONE, FARZAN ROHANI We were part of a team of data scientists in Search Infrastructure at Google that took on the task of developing robust and automatic large-scale time series forecasting for our organization. So it should come as no surprise that Google has compiled and forecast time series for a long time.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Sisense

JULY 15, 2020

The model outputs the 4 following time series: S – The number of Susceptible individuals E – The number of people Exposed to an infected individual and are potential carriers I – Infected individuals R – Recovered individuals. Calling on Quest to handle complex calculations with ease.

Analytics 90

Analytics Modeling Visualization Dashboards 90

DataRobot Blog

DECEMBER 15, 2022

AI-powered Time Series Forecasting may be the most powerful aspect of machine learning available today. Working from datasets you already have, a Time Series Forecasting model can help you better understand seasonality and cyclical behavior and make future-facing decisions, such as reducing inventory or staff planning.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

Sisense

JUNE 26, 2020

Both Python and R are advanced coding languages that can produce beautiful images that allow humans to understand vast datasets with ease. As datasets become bigger and more complex, only AI, materialized views, and more sophisticated coding languages will be able to glean insights from them. The good news is, you don’t have to!

Visualization 97

Visualization Unstructured Data Measurement Data-driven 97

Cloudera

MAY 3, 2021

Real-time and time series data is growing 50% faster than static data forms and streaming analytics is projected to grow at a 34% CAGR. Moving to real-time data flows is an opportunity to connect new streaming data sources to the data lifecycle, which did not fit the previous batch model. trillion in value by 2025.”,

Cost-Benefit 103

Cost-Benefit Digital Transformation Data Lake Enterprise 103

Cloudera

SEPTEMBER 20, 2022

This blog is intended to serve as an ethics sheet for the task of AI-assisted comic book art generation, inspired by “ Ethics Sheets for AI Tasks.” AI-assisted comic book art generation is a task I proposed in a blog post I authored on behalf of my employer, Cloudera. It can take a long time and a lot of practice. Introduction.

Deep Learning 88

Deep Learning Cost-Benefit Risk Data-driven 88

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

This blog post motivates this problem more fully, and discusses monotonic splines and lattices as a solution. While the discussion is about methods and applications, the blog also contains pointers to research papers and to the TensorFlow Lattice package that provides an implementation of these solutions. But we also know more.

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

Cloudera

SEPTEMBER 24, 2021

Initially, network monitoring and service assurance systems like network probes tended not to persist information: they were designed as reactive, passive monitoring tools that would allow you to see what was going on at a point in time, after a network problem had occurred, but the data was never retained.

Analytics 96

Analytics IoT Cost-Benefit Big Data 96

Data Science and Beyond

JANUARY 7, 2019

Instead, all one needs to do is resample the given data many times, and calculate the desired statistics. We take r bootstrap resamples from the original data sample, where each resample is a sample with replacement of size n. However, I’ve learned in the past few weeks that there are quite a few pitfalls in bootstrapping.

Statistics 77

Statistics Uncertainty Testing Modeling 77

Cloudera

FEBRUARY 8, 2021

Continuing from my previous blog post about how awesome and easy it is to develop web-based applications backed by Cloudera Operational Database (COD), I started a small project to integrate COD with another CDP cloud experience, Cloudera Machine Learning (CML). . For this purpose, I will use the LSTM (Long Short-term memory) algorithm.

Machine Learning 75

Machine Learning Statistics Dashboards Modeling 75

Darkhorse

DECEMBER 11, 2017

I suggest that there are five distinct job descriptions: SUBSCRIBE TO OUR BLOG. He’ll use tools such as TensorFlow, R, MATLAB, ArcInfo, SAS, Tableau, and SPSS. He makes sure that results are timely and fast. In other instances, organizations will try to shoehorn engineers into the roles “in their spare time”.

Analytics 80

Analytics Visualization Data Warehouse Data Science 80

AWS Big Data

MAY 4, 2023

Traditional solutions in use today, particularly with climate data, are time consuming and unsustainable, replicating datasets cross Regions. Amazon’s Open Data Sponsorship Program allows organizations to host free of charge on AWS. The AWS CDK solution deploys a network of Dask workers across two AWS Regions, connecting into a client Region.

Data Processing 121

Data Processing Metadata Informatics Interactive 121

DataRobot

APRIL 26, 2021

Demand forecasting is a common Time Series use case in DataRobot. In this blog post, we describe these strategies. However, it shouldn’t be too hard to achieve with Python or R. After several iterations of XGB estimation, series that have similar model performance are then assigned to individual clusters.

Forecasting 59

Forecasting Sales Data-driven Modeling 59

Sisense

MAY 26, 2020

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. It locates and classifies different entities such as person names, organizations, locations, time expressions, quantities, monetary values, and percentages. Real-time data.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

Sisense

JANUARY 15, 2021

But in this second post in our Building Bridges series, we are focused on the data teams driving the adoption of a BI and analytics tool with their business intelligence counterparts. Big data is now modeled and queried using advanced coding languages like SQL, Python, and R. Implementing analytics at your company is a multi-team job.

Analytics 75

Analytics Data-driven Business Intelligence Visualization 75

IBM Big Data Hub

AUGUST 24, 2023

In June, we took a major step in our journey by conducting a series of air bound tests dubbed “SpaceDucks 3” in San Luis Obispo, CA. We’re pleased to report that we successfully launched six balloons, including a group of five mesh SpaceDucks at one time. Air Force to thank as part of the R&D funding as well.

IT 67

IT Testing Dashboards Visualization 67

Sisense

AUGUST 9, 2021

>>>Reveal deeper intelligence from your data with Python and R. . >>>Reveal >>>Reveal deeper intelligence from your data with Python and R. Pat Bhatt (PB): The Notebooks functionality empowers data analysts with the tools they need to conduct advanced analysis using SQL, Python, and R.

Analytics 52

Analytics Visualization Marketing Data Warehouse 52

Jedox

MARCH 12, 2020

Renewing business technologies that have slowly seen their value erode over time or become problematic ultimately means added value for your organization. Employees need time to get familiar with new solutions, data must be migrated and so on. This blog post is part of our series on EPM Tech Refresh.

Forecasting 59

Forecasting Optimization Technology Modeling 59

Smarten

JULY 30, 2024

Your users can access: Time Series Forecasting Regression Techniques Classification Association Correlation Clustering Hypothesis Testing Descriptive Statistics ‘Assisted predictive modeling can take the guesswork out of analytics, by helping users to choose the right techniques to analyze the type and volume of data they use to analyze.’

Predictive Analytics 62

Predictive Analytics Prescriptive Analytics Predictive Modeling Analytics 62

Cloudera

SEPTEMBER 23, 2020

You can find part 1 of this series, here. . Apache Ranger fine-grained policies enable dynamic row filtering through SQL query compile time when SQL based relational constructs are used on OpDB (Hive on HBase). We are going to talk about auditing, different security levels, security features of Data Catalog, and Client Considerations.

Data Lake 84

Data Lake Metadata IoT Enterprise 84

Smarten

MAY 13, 2024

Studies reveal that most PMML Integration tools provide support for numerous types of predictive analytical models, tools and techniques including: Logistical Regression Linear Regression Decision Tree Clustering Time Series …etc. PMML Integration can and should support platforms like Python, R, Java, KNIME, etc.

Predictive Modeling 62

Predictive Modeling Data mining Predictive Analytics Modeling 62

IBM Big Data Hub

SEPTEMBER 28, 2023

They also need secured access to business-relevant models that can help accelerate time to value and insights. emerges as a compelling solution,” says Atsushi Hasegawa, Chief Engineer, Honda R&D. emerges as a compelling solution,” says Atsushi Hasegawa, Chief Engineer, Honda R&D.

Testing 87

Testing Finance Enterprise Modeling 87

Sisense

DECEMBER 11, 2019

In our Event Spotlight series, we cover the biggest industry events helping builders learn about the latest tech, trends, and people innovating in the space. With data growing at a staggering rate, managing and structuring it is vital to your survival. In this piece, we detail the Israeli debut of Periscope Data. What VCs want from startups.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

The Unofficial Google Data Science Blog

MARCH 13, 2017

By MUKUND SUNDARARAJAN, ANKUR TALY, QIQI YAN Editor's note: Causal inference is central to answering questions in science, engineering and business and hence the topic has received particular attention on this blog. coefficient times feature value) would be indicative of what the model deemed noteworthy.

IT 70

IT Visualization Modeling Uncertainty 70

The Unofficial Google Data Science Blog

SEPTEMBER 30, 2016

Editor's note: The Google Sheets add-on described in this blog post is no longer supported externally by Google. While big data remains a focus of this blog, there are exciting innovations happening in other areas as well. hope to replace R, SAS, or similar packages designed by and for statistics experts. By STEVEN L.

Statistics 55

Statistics Big Data Data Science Marketing 55

Jet Global

AUGUST 28, 2020

Blog posts : 99. R Ray Wang has held executive roles in product, marketing, strategy, and consulting at companies such as Forrester Research, Oracle, PeopleSoft, Deloitte, Ernst & Young, Personify, and Johns Hopkins Hospital. Blog posts : 13. Book Credits : – Blog posts : 32. Score : 4.0. YouTube Videos : 73.

Sales 52

Sales Manufacturing Strategy Marketing 52

DataRobot Blog

NOVEMBER 3, 2022

Data scientists have used the DataRobot AI Cloud platform to build time series models for several years. However, tedious and redundant tasks in exploratory data analysis, model development, and model deployment can stretch the time to value of your machine learning projects. That’s not because people aren’t intelligent.

Forecasting 52

Forecasting Sales Modeling Data-driven 52

AWS Big Data

JUNE 7, 2023

This is a guest blog post co-written with Sumesh M R from Cargotec and Tero Karttunen from Knowit Finland. In this blog, we discuss the technical challenges faced by Cargotec in replicating their AWS Glue metadata across AWS accounts, and how they navigated these challenges successfully to enable cross-account data sharing.

Metadata 58

Metadata Data Lake Machine Learning Big Data 58

Domino Data Lab

AUGUST 6, 2021

This is an extremely time-consuming and inefficient process that would be much more efficient using an ML model. Missing data needs to be addressed, data needs to be categorized, extraneous data and duplicate columns need to be removed, and only data that is available during the time of prediction may be used. Identify the Problem.

Data Science 75

Data Science Testing Modeling Publishing 75

Cloudera

MAY 28, 2019

Most would maintain that the majority of data scientists’ time is still spent on collecting and preparing data for analysis. Most would maintain that the majority of data scientists’ time is still spent on collecting and preparing data for analysis. Data management for ML/AI – what’s the big deal? Stay tuned. Register today!

Data Science 50

Data Science Machine Learning Data Strategy Cost-Benefit 50