Rocket-Powered Data Science

APRIL 25, 2019

Learn the what, why, and how of Data Science and Machine Learning here. Follow Kirk Borne on Twitter @KirkDBorne.

Data Science 38

Data Science Machine Learning Deep Learning Statistics 38

Smart Data Collective

AUGUST 20, 2021

As we said in the past, big data and machine learning technology can be invaluable in the realm of software development. Machine learning technology has become a lot more important in the app development profession. Machine learning can be surprisingly useful when it comes to monetizing apps.

Machine Learning 90

Machine Learning Data mining Advertising Deep Learning 90

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

JUNE 7, 2022

It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. What are the four types of data analytics?

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

datapine

MARCH 25, 2019

What Is A Data Analysis Method? Data analysis method focuses on strategic approaches to taking raw data, mining for insights that are relevant to the business’s primary goals, and drilling down into this information to transform metrics, facts, and figures into initiatives that benefit improvement.

Key Performance Indicator 217

Key Performance Indicator Statistics Big Data Visualization 217

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 141

Optimization Machine Learning Data mining Statistics 141

Jen Stirrup

SEPTEMBER 30, 2021

Although CRISP-DM is not perfect , the CRISP-DM framework offers a pathway for machine learning using AzureML for Microsoft Data Platform professionals. AI vs ML vs Data Science vs Business Intelligence. They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

CIO Business Intelligence

NOVEMBER 14, 2022

Decision support systems are generally recognized as one element of business intelligence systems, along with data warehousing and data mining. They generally leverage simple statistical and analytical tools, but Power notes that some OLAP systems that allow complex analysis of data may be classified as hybrid DSS systems.

Data mining 144

Data mining Data-driven Statistics OLAP 144

Smart Data Collective

JUNE 4, 2021

These data models predict outcomes of new data. Data science is one of the highest-paid jobs of the 21st century. Data science needs knowledge from a variety of fields including statistics, mathematics, programming, and transforming data. Here are the chronological steps for the data science journey.

Data Science 133

Data Science Statistics Deep Learning Machine Learning 133

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. Tableau: Now owned by Salesforce, Tableau is a data visualization tool.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

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. On premises or in SAP cloud. Per user, per month.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. from 2022 to 2028.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

Data Science 101

DECEMBER 11, 2019

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Every year they host an excellent and influential conference focusing on many areas of data science. Honestly, KDD has been promoting data science way before data science was even cool. 1989 to be exact. The details are below.

KDD 81

KDD Knowledge Discovery Data mining Data Science 81

datapine

MARCH 25, 2022

There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. But let’s see in more detail what experts say and how can we connect and differentiate the both.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

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 139

Predictive Analytics Analytics Predictive Modeling Data mining 139

datapine

MARCH 31, 2022

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. This beats projections for almost all other occupations. BI engineer.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

CIO Business Intelligence

JANUARY 19, 2024

Companies are increasingly eager to hire data professionals who can make sense of the wide array of data the business collects. The US Bureau of Labor Statistics (BLS) forecasts employment of data scientists will grow 35% from 2022 to 2032, with about 17,000 openings projected on average each year.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

FineReport

MAY 6, 2020

Software Pemvisualisasi Data: excel, python, software profesional lainnya. Framework Big Data Processing: Hadoop, storm, spark. Data Warehous: SSIS, SSAS. Machine learning. Skill Data Mining: Matlab, R, Python. Seperti yang Anda ketahui, statistik adalah dasar analisis data. Tulis Laporan.

Data mining 98

Data mining Data Warehouse Machine Learning Big Data 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. Organization: Columbia University Price: Students pay Columbia Engineering’s rate of tuition (US$2,362 per credit).

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

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 99

Big Data Software Data mining Prescriptive Analytics 99

CIO Business Intelligence

DECEMBER 22, 2022

Such teams tend to view analytic pipelines as analogous to lean manufacturing lines and regularly reflect on feedback provided by customers, team members, and operational statistics. The DataOps approach is not limited to machine learning,” they add.

Analytics 130

Analytics Machine Learning Data mining Software 130

CIO Business Intelligence

JANUARY 20, 2023

BI focuses on descriptive analytics, data collection, data storage, knowledge management, and data analysis to evaluate past business data and better understand currently known information. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

Smart Data Collective

MARCH 23, 2020

Online shopping, gaming, web surfing – all of this data can be collected, and more importantly, analyzed. Most businesses prefer to rely on the insights gained from the big data analysis. With the help of data mining and machine learning, it is now possible to find the connections between seemingly disparate pieces of information.

Big Data 131

Big Data Recreation/Entertainment Data mining Optimization 131

CIO Business Intelligence

OCTOBER 13, 2023

Information/data governance architect: These individuals establish and enforce data governance policies and procedures. Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

Smart Data Collective

OCTOBER 17, 2022

It gives data scientists the best way to manipulate data sources so that they can eventually spot anomalies, test hypotheses, discover patterns, and even check assumptions Machine learning is a type of AI that focuses on the use of algorithms and data to replicate the way a human brain thinks works and makes decisions.

Data Warehouse 145

Data Warehouse Data Lake Visualization Big Data 145

datapine

SEPTEMBER 27, 2022

Recently published in 2021, “SQL for Data Scientists” by author and experienced data scientist, Rénee Teate, teaches its readers all the skills that data scientists use the most in their daily work. Originally published in 2018, the book has a second edition that was released in January of 2022.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

CIO Business Intelligence

AUGUST 9, 2022

According to data from PayScale , the following data engineering skills are associated with a significant boost in reported salaries: Ruby: +32% Oracle: +26% MapReduce: +26% JavaScript: +24% Amazon Redshift: +21% Apache Cassandra: +18% Apache Sqoop: +12% Data Quality: +11% Apache HBase: +10% Statistical Analysis: +10% Data engineer certifications.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

CIO Business Intelligence

AUGUST 11, 2023

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. Licensed by MIT, SpaCy was made with high-level data science in mind and allows deep data mining.

Unstructured Data 142

Unstructured Data Machine Learning Data Science Data mining 142

FineReport

JUNE 11, 2021

But more specifically, it represents the toolkits that leaders employ when they want to collect and manage data assets produce informative reports to optimize the current workflows. Business analytics is how companies use statistical methods and techniques to analyze historical data to gain new insights and improve strategic decision-making.

Business Intelligence 98

Business Intelligence Analytics Dashboards Statistics 98

Smart Data Collective

MAY 8, 2022

Let’s not forget that big data and AI can also automate about 80% of the physical work required from human beings, 70% of the data processing, and more than 60% of the data collection tasks. From the statistics shown, this means that both AI and big data have the potential to affect how we work in the workplace.

Big Data 122

Big Data Data Analytics Analytics Cost-Benefit 122

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 353

Data Science Analytics Data mining Deep Learning 353

FineReport

JULY 28, 2021

Definition: BI vs Data Science vs Data Analytics. Business Intelligence describes the process of using modern data warehouse technology, data analysis and processing technology, data mining, and data display technology for visualizing, analyzing data, and delivering insightful information.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

Smart Data Collective

AUGUST 11, 2022

One of the best benefits involves using data analytics to improve cash collection processes. Data Analytics Helps Companies Create Better Cash Collection Strategies. However, statistics have shown that many businesses don’t receive customer payments on time. Data analytics can help you automate these adjustments.

Data Analytics 128

Data Analytics Optimization Analytics Cost-Benefit 128

BizAcuity

APRIL 28, 2019

Today, it’s no secret that most forward-thinking businesses are keenly following the latest developments on big data, artificial intelligence, machine learning, and predictive analytics. And for that, they are looking up to new-age technologies. One such interesting case study is WNS.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

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 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Sisense

APRIL 10, 2020

R is a tool built by statisticians mainly for mathematics, statistics, research, and data analysis. These visualizations are useful for helping people visualize and understand trends , outliers, and patterns in data. Some standard Python libraries are Pandas, Numpy, Scikit-Learn, SciPy, and Matplotlib.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98