CIO Business Intelligence

APRIL 22, 2022

What is data science? Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Data science gives the data collected by an organization a purpose. Data science vs. data analytics.

Data Science 137

Data Science Statistics Machine Learning Visualization 137

Data Science 101

OCTOBER 31, 2019

This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Machine learning provides the technical basis for data mining.

Data mining 77

Data mining KDD Data Science Forecasting 77

Analytics Vidhya

DECEMBER 13, 2021

Pursuing any data science project will help you polish your resume. The post Top Data Science Projects to add to your Portfolio in 2021 appeared first on Analytics Vidhya. Introduction 2021 is a year that proved nothing is better than a Proof of Work to evaluate any candidate’s worth, initiative, and skill.

Data Science 334

Data Science Analytics Data mining Deep Learning 334

FineReport

JULY 28, 2021

Good data can give you keen insights, convincing evidence to make informed decisions. By observing and analyzing data, we can develop more accurate theories and formulate more effective solutions. For this reason, data science and/vs. Definition: BI vs Data Science vs Data Analytics.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

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 125

Big Data Data Analytics Analytics Predictive Modeling 125

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. These data models predict outcomes of new data. Where to start?

Data Science 104

Data Science Statistics Deep Learning Machine Learning 104

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 57

Data Science Machine Learning Cost-Benefit Deep Learning 57

Analytics Vidhya

MAY 4, 2022

This article was published as a part of the Data Science Blogathon. Introduction Text Mining is also known as Text Data Mining or Text Analytics or is an artificial intelligence (AI) technology that uses natural language processing (NLP) to extract essential data from standard language text.

Unstructured Data 249

Unstructured Data Data mining Data Science Publishing 249

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics methods and techniques.

Data Analytics 127

Data Analytics Diagnostic Analytics Management Analytics 127

CIO Business Intelligence

NOVEMBER 14, 2022

With organizations increasingly focused on data-driven decision making, decision science (or decision intelligence) is on the rise, and decision scientists may be the key to unlocking the potential of decision science systems. It features support for creating and visualizing decision tree–driven customer interaction flows.

Data mining 127

Data mining Data-driven Statistics OLAP 127

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data Architecture 126

Data Architecture Data Warehouse Statistics Visualization 126

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). Examples: (1-3) All those applications shown in the definition of Machine Learning. (4)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. Visual IDE for data pipelines; RPA for rote tasks.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

Smart Data Collective

DECEMBER 19, 2021

The rise of machine learning and the use of Artificial Intelligence gradually increases the requirement of data processing. That’s because the machine learning projects go through and process a lot of data, and that data should come in the specified format to make it easier for the AI to catch and process.

Optimization 135

Optimization Machine Learning Data mining Statistics 135

FineReport

MARCH 24, 2024

Daily, data analysts engage in various tasks tailored to their organization’s needs, including identifying efficiency improvements, conducting sector and competitor benchmarking, and implementing tools for data validation. BI tools : Enables data aggregation, analysis, and visualization through dashboards and shared reports.

Statistics 52

Statistics Data mining Visualization Reporting 52

Cloudera

OCTOBER 31, 2023

This kind of question lends itself perfectly to data science approaches that enable quick and intuitive analysis of data across multiple sources. They released a blog this year with the results from their annual data mining, it includes the top 3 candies purchased for each state and the quantity purchased in pounds.

Data mining 77

Data mining Machine Learning Data Science Sales 77

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer vs. data architect.

Analytics 121

Analytics Data Science Statistics Unstructured Data 121

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

Cloudera

OCTOBER 26, 2021

This kind of question lends itself perfectly to data science approaches that enable quick and intuitive analysis of data across multiple sources. They released a blog this year with the results from their annual data mining, it includes the top 3 candies purchased for each state and the quantity purchased in pounds.

Data mining 101

Data mining Machine Learning Data Science Sales 101

Smart Data Collective

NOVEMBER 12, 2022

As a data analyst, you will learn several technical skills that data analysts need to be successful, including: Programming skills. Machine learning knowledge. Data visualization capability. Data Mining skills. Data wrangling ability.

Sales 115

Sales Data mining Data-driven Data Analytics 115

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

datapine

MARCH 31, 2022

To simplify things, you can think of back-end BI skills as more technical in nature and related to building BI platforms, like online data visualization tools. Front-end analytical and business intelligence skills are geared more towards presenting and communicating data to others. b) If You’re Already In The Workforce.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Smart Data Collective

OCTOBER 14, 2019

Whether they want a career as an app developer or data analyst, the skillsets below can help them find lucrative careers in a competitive job market. Big Data Skillsets. From artificial intelligence and machine learning to blockchains and data analytics, big data is everywhere. Machine Learning.

Big Data 75

Big Data Software Data mining Prescriptive Analytics 75

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? Data analysis and interpretation The next step is to examine the extracted patterns, trends and insights to develop meaningful conclusions.

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

FineReport

DECEMBER 19, 2019

Professional data analysts must have a wealth of business knowledge in order to know from the data what has happened and what is about to happen. In addition, tools for data analysis and data mining are also important. Excel, Python, Power BI, Tableau, FineReport are frequently used by data analysts.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

CIO Business Intelligence

MARCH 24, 2023

SAS Data Management Built on the SAS platform, SAS Data Management provides a role-based GUI for managing processes and includes an integrated business glossary, SAS and third-party metadata management, and lineage visualization. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

Data Governance 142

Data Governance Management Metadata Data Quality 142

erwin

JUNE 11, 2020

Transforming Industries with Data Intelligence. Data intelligence has provided useful and insightful information to numerous markets and industries. With tools such as Artificial Intelligence, Machine Learning, and Data Mining, businesses and organizations can collate and analyze large amounts of data reliably and more efficiently.

Key Performance Indicator 103

Key Performance Indicator KPI Data-driven Machine Learning 103

Ontotext

APRIL 15, 2020

GraphDB’s Visual Graph can be used to explore the data as demonstrated below. As this type of data is very dynamic, the flexibility of knowledge graphs and their capacity to seamlessly integrate data from disparate sources provides researchers with valuable live insights into the COVID-19 pandemic and its consequences.

Publishing 105

Publishing Metadata Data mining Technology 105

Decision Management Solutions

DECEMBER 12, 2018

As they quote in the paper: According to the Rexer Data Science Survey, barely 10 to 15% of companies “almost always” deploy results and another 50% only deploy “often.” Begin with an agile analytic deployment platform, not with visualization. Focus on continuous improvement and how you will learn and improve.

Analytics 40

Analytics Predictive Analytics Modeling Data-driven 40

Edwin Chen

SEPTEMBER 6, 2011

tl;dr See this movie visualization for a case study on how a post propagates through Quora. A machine learning group of folks in orange centered around people like Oliver Grisel, Christian Langreiter, and Joseph Turian. Here’s a visualization I made of upvotes on my answer across time (click here for a larger view).

Machine Learning 52

Machine Learning Broadcasting Visualization Data mining 52

CIO Business Intelligence

JANUARY 20, 2023

But the benefits of BI extend beyond business decision-making, according to data visualization vendor Tableau , including the following: Data-driven business decisions: The ability to drive business decisions with data is the central benefit of BI.

Business Intelligence 139

Business Intelligence Dashboards Data mining OLAP 139

datapine

AUGUST 29, 2022

James Warren, on the other part, is a successful analytics architect with a background in machine learning and scientific computing. 5) Data Analytics Made Accessible, by Dr. Anil Maheshwari. Best for : the new intern who has no idea what data science even means. The author, Anil Maheshwari, Ph.D.,

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Domino Data Lab

MAY 20, 2021

Machine Learning algorithms often need to handle highly-imbalanced datasets. Figure 3 shows visual explanation of how SMOTE generates synthetic observations in this case. A weighted nearest neighbor algorithm for learning with symbolic features. Machine Learning, 57–78. UCI machine learning repository.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

CIO Business Intelligence

NOVEMBER 28, 2023

Continuing with his example, Minarik points out the valuable role AI and machine learning play in analyzing unstructured data streams over time. “It Ensure value with visualizations. The process of making unstructured data usable doesn’t end with analysis, Minarik says. Data Management, Data Mining, Data Science

Unstructured Data 122

Unstructured Data Data-driven Visualization Data Quality 122

FineReport

JULY 18, 2022

The features you or your company need are core factors influencing your selection of the data analytics tool. For example, if you want the features of data visualization , such as stunning dashboards and rich charts, business intelligence tools are more suitable for you than a pure programming tool. Free Download. From FineBI.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

CDW Research Hub

DECEMBER 4, 2019

Universal data fabric : With the explosive growth of data in all different forms—structured, semi-structured and unstructured—there is a need to work with massive amounts of data, mine it, and make it easily accessible so one can gather intelligence and analytics out of it.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

BizAcuity

MARCH 31, 2022

AI can be applies to all 3 major types of analytics: Descriptive Analytics: The entire journey of the descriptive and diagnostic analytics process includes data extraction, data aggregation and data mining; 3 applications where AI is widely used to reduce costs, and eliminate complex actions. AI Services.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52