Analytics Vidhya

SEPTEMBER 8, 2022

Introduction A lead in a business, also known as a sales lead, is a user or a potential customer who has shown interest in what your company has to offer. The post Exploratory Data Analysis (EDA) on Lead Scoring Dataset appeared first on Analytics Vidhya. Leads […].

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Sales Analytics Visualization Data Science 294

Analytics Vidhya

SEPTEMBER 9, 2021

This article was published as a part of the Data Science Blogathon What is Hypothesis Testing? Any data science project starts with exploring the data. When we perform an analysis on a sample through exploratory data analysis and inferential statistics we get information about the sample.

Machine Learning 311

Machine Learning Testing Statistics Data Science 311

KDnuggets

AUGUST 1, 2023

A Data Scientist’s Essential Guide to Exploratory Data Analysis GPT4All is the Local ChatGPT for your Documents and it is Free!

IT 88

IT Data Science 88

Juice Analytics

DECEMBER 24, 2021

?? Exploratory data analysis is.the "herding cats" ?? stage of working with data. Without exploring and understanding your data, you cannot move on to explaining it to others. ?? Explanatory data presentation is.the "herding cows" ?? stage of working with data. Source: Forbes. ?? + ??

Interactive 137

Interactive Measurement Visualization Reporting 137

Cloudera

OCTOBER 4, 2023

Fast moving data and real time analysis present us with some amazing opportunities. Every organization has some data that happens in real time, whether it is understanding what our users are doing on our websites or watching our systems and equipment as they perform mission critical tasks for us.

Data Warehouse 83

Data Warehouse Experimentation Cost-Benefit Dashboards 83

Cloudera

JUNE 3, 2022

Data scientists and machine learning engineers in enterprise organizations need to fully understand their data in order to properly analyze it, build models, and power machine learning use cases across their business. Data scientists are likely to use a variety of different tools to move through their processes.

Dashboards 88

Dashboards Visualization Machine Learning Data Science 88

Juice Analytics

SEPTEMBER 26, 2022

Let the data run free! Government organizations, academic institutions, non-profits, and even passionate sports fans are gathering and sharing valuable data sets with the public. It is a powerful way to support a cause and encourage data-driven analysis. Simply posting the data in a searchable format isn’t enough.

Visualization 120

Visualization Advertising Metrics Interactive 120

Juice Analytics

NOVEMBER 2, 2021

How to get started with data storytelling? For the beginner — and even for the experienced data analyst or data scientist — data storytelling can be a vague, disorientating concept. The “last mile” of analytics Data storytelling is about helping make your work pay off. What are their priorities?

Broadcasting 138

Broadcasting Visualization Interactive Analytics 138

Juice Analytics

MARCH 9, 2021

We created Juicebox to serve the citizen data analyst. We empathize with the every-person who is deep in Excel spreadsheets and presentations; data is part of their job--but not the only part. We want to give these people the chance to create beautiful data visualizations, presented alongside their messages and insights.

Interactive 113

Interactive Dashboards Visualization Marketing 113

Smart Data Collective

JUNE 4, 2021

What is data science? Data science is analyzing and predicting data, It is an emerging field. Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Data scientists use algorithms for creating data models. Where to start?

Data Science 105

Data Science Statistics Deep Learning Machine Learning 105

Juice Analytics

JUNE 2, 2022

The same is true about delivering data to your customers. It is a delightful journey through personalized data and a reminder of how much you have enjoyed the service throughout the year. It is a delightful journey through personalized data and a reminder of how much you have enjoyed the service throughout the year.

Broadcasting 129

Broadcasting Visualization Reporting Metrics 129

Data Science 101

APRIL 26, 2019

While it is not one of the popular programming languages for data science, The Go Programming Language (aka Golang) has surfaced for me a few times in the past few years as an option for data science. I decided to do some searching and find some conclusions about whether golang is a good choice for data science.

Data Science 111

Data Science Machine Learning Interactive Risk 111

Perceptual Edge

FEBRUARY 19, 2018

I am often asked a version of the following question: “What data visualization product do you recommend?” My response is always the same: “That depends on what you do with data.” I think this was, in part, because he and many others like him don’t think of what they do with data as consisting of different types of tasks.

Statistics 60

Statistics Dashboards Reporting Sales 60

FineReport

DECEMBER 19, 2019

For super rookies, the first task is to understand what data analysis is. Data analysis is a type of knowledge discovery that gains insights from data and drives business decisions. One is how to gain insights from the data. Data is cold and can’t speak. How do I learn, and to what extent?

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Cloudera

SEPTEMBER 22, 2022

We’ve previously highlighted opportunities to improve digital claims processing with data and AI. To me, this means that by applying more data, analytics, and machine learning to reduce manual efforts helps you work smarter. Step one: gather the data. Utilizing a variety of data sources creates a more accurate picture of risks.

Analytics 95

Analytics Insurance IoT Risk 95

CIO Business Intelligence

MAY 1, 2023

The conversations reminded everyone that there isn’t a one-size-fits-all approach to the journey and that each organization should focus on its operating model, the architecture of the organization, and the availability, accessibility, and necessity for data to help inform the decision-making processes.

Consulting 59

Consulting Data Governance Digital Transformation ROI 59

Smart Data Collective

MARCH 13, 2020

It doesn’t matter what the project or desired outcome is, better data science workflows produce superior results. 5 Tips for Better Data Science Workflows. Data science is a complex field that requires experience, skill, patience, and systematic decision-making in order to be successful. Phase 2: Exploratory Data.

Data Science 101

Data Science Key Performance Indicator Knowledge Discovery Visualization 101

Domino Data Lab

MARCH 3, 2021

In some cases, data science does generate models directly to revenue, such as a contextual deal engine that targets people with offers that they can instantly redeem. But what about good decisions? Align on key indicators of success during the initiation phase of a data science project.

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Metrics Modeling Sales Data Science 93

The Unofficial Google Data Science Blog

OCTOBER 31, 2016

By PATRICK RILEY For a number of years, I led the data science team for Google Search logs. Some people seemed to be naturally good at doing this kind of high quality data analysis. But what do those adjectives actually mean? What actions earn you these labels? Something like histograms, CDFs, Q-Q plots, etc.

Metrics 107

Metrics Measurement Statistics Data Collection 107

DataRobot

DECEMBER 20, 2021

We collect more and more diverse data types, and we’re not always sure how we can turn this data into real value. Or even if we have a pretty good understanding of the problem, there is not enough data to run a successful project and deliver impact back to the business. Who Can Benefit from the Visual Data?

Visualization 97

Visualization Deep Learning Machine Learning Modeling 97

Alation

OCTOBER 7, 2021

Jason McVay is a data scientist at Indigo Ag, an agriculture-tech company headquartered in Massachusetts. In this essay, Jason reflects on the value of thinking spatially about data, showing how his experience as a graduate student influences his role as a data scientist today. The rise of spatial data. It is essential.

Data Lake 98

Data Lake Visualization Data Science Digital Transformation 98

Rocket-Powered Data Science

JULY 7, 2019

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics).

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

FineReport

MARCH 29, 2023

In this article, we will introduce what Qlik Sense is, the differences and connections between Qlik Sense and QlikView, and how it compares to the leading BI tool in Asia: FineReport. Qlik Sense supports a comprehensive range of analysis scenarios. Data source support FineReport supports more database connections than Qlik Sense.

Reporting 52

Reporting Visualization Dashboards Enterprise 52

3AG Systems

DECEMBER 1, 2018

What is ad hoc analysis and ad hoc reporting? In a world where businesses live or die on data, self service BI is the information super-food we’ve been waiting for. So what is ad hoc analysis? Exactly what the name implies — reporting prepared for a specific or immediate need. Read More

IT 40

IT Business Intelligence Data Collection Interactive 40

3AG Systems

OCTOBER 1, 2018

The ad hoc promise In a world where businesses live or die on data, self-serve BI is the information super-food we’ve been waiting for. Central to this promise is that any employee who wants to can collect and analyze company data on their own. What self-serve BI does well Maybe; it depends on what you want it to do.

Business Intelligence 40

Business Intelligence Data Collection Interactive Reporting 40

Jet Global

DECEMBER 3, 2021

The term “ business intelligence ” (BI) has been in common use for several decades now, referring initially to the OLAP systems that drew largely upon pre-processed information stored in data warehouses. Discover Meaning Amid All That Data. In short, it’s the exploratory character of truly great BI tools that makes them so powerful.

Business Intelligence 52

Business Intelligence Sales OLAP Data Warehouse 52

Alation

MAY 17, 2022

An enterprise data catalog is one such key asset. The Data Analyst Workflow. The workflow of a data analyst consists of four key stages: Discovery. When a businessperson poses a question to an analyst, the analyst starts by trying to find the right data. 7 Steps that Benefit from a Data Catalog. Preparation.

Metadata 52

Metadata Data Quality Machine Learning Reporting 52

Business Over Broadway

MARCH 13, 2019

Customer experience management (CXM) programs are necessarily a quantitative endeavor, requiring CX professionals to decipher insights from a sea of customer data. Customer Experience Management (CXM) programs rely on different types of data that come from a variety of sources. Case Study: The Survey Data. Why IBM Watson Studio?

Statistics 78

Statistics Measurement Descriptive Analytics Machine Learning 78

FineReport

MARCH 17, 2024

This article aims to provide a detailed interpretation of the various elements of the boxplot, along with analysis and creation techniques, to aid in your journey as a data analyst. What is a Boxplot? Firstly, what is a boxplot? How do we analyze the data in a boxplot? Maximum value = Q3 + 1.5 * IQR.

Statistics 98

Statistics Visualization Reporting Software 98

AWS Big Data

JANUARY 24, 2023

Reporting and analysis – An application where you can trigger large analytical queries with dynamic inputs and then view or download the results. Data abstraction – Decouple and refactor underlying data structure and infrastructure. The Data API takes care of managing database connections and buffering data.

Analytics 58

Analytics Data-driven Management Reporting 58

Domino Data Lab

NOVEMBER 17, 2020

It is hoped this data will give researchers a better understanding of what they are studying. Classical statistics, developed in the 20 th century for small datasets, do not work for data where the number of variables is much larger than the number of samples (Large P Small N, Curse of Dimensionality, or P >> N data).

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

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. Data poisoning attacks. Data poisoning attacks have also been called “causative” attacks.)

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. The Importance of Exploratory Analytics in the Data Science Lifecycle. Exploratory analysis is a critical component of the data science lifecycle. But what about the costs involved with doing so, “properly”? imputation of missing values).

Statistics 106

Statistics Unstructured Data Data Science Predictive Modeling 106

datapine

APRIL 15, 2020

When encouraging these BI best practices what we are really doing is advocating for agile business intelligence and analytics. What Is Agile Analytics And BI? When it comes to implementing and managing a successful BI strategy we have always proclaimed: start small, use the right BI tools , and involve your team. Source: www.pmi.org.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

datapine

OCTOBER 30, 2019

Historically, the terms data report or business report haven’t got the crowds excited. Data reports have always been important for businesses. The business intelligence industry has been revolutionized over the past decade and data reports are in on the fun. Read on to see why data reports matter and our top data reporting tips.

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Reporting Visualization Dashboards KPI 127

Juice Analytics

DECEMBER 1, 2020

The hot new concept in data visualization is "data storytelling"; some are calling it the next evolution of visualization (I'm one of them). However, we're early in the discussion and there are more questions than answers: Is data storytelling more than a catchy phrase? Data scientists aren’t always up to the job.”

Visualization 133

Visualization Interactive Uncertainty Data-driven 133

IBM Big Data Hub

DECEMBER 20, 2023

What is machine learning? ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. In other words, ML leverages input data to predict outputs, continuously updating outputs as new data becomes available.

Machine Learning 82

Machine Learning Modeling Deep Learning Predictive Modeling 82