ODSC - Open Data Science

FEBRUARY 2, 2023

Analytics and Data Analysis Coming in as the 4th most sought-after skill is data analytics, as many data scientists will be expected to do some analysis in their careers. Scikit-learn also earns a top spot thanks to its success with predictive analytics and general machine learning.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

Data Science Connect

JULY 26, 2023

Data-Driven Approaches to Cybersecurity and Sustainability Data scientists play a critical role in harnessing the power of data to improve both cybersecurity and sustainability efforts. Identifying potential attacks in advance allows organizations to take proactive measures and prevent security breaches.

Data Scientist 130

Data Scientist Predictive Analytics Internet of Things Artificial Intelligence 130

Pickl AI

JUNE 4, 2024

Data collection from smart meters, weather stations, and sensors empowers us to predict energy demand and production. Data visualization tools translate complex data into clear visuals, fostering stakeholder engagement and driving progress towards a clean energy future.

Analytics 52

Analytics Analytics Predictive Analytics Data Visualization 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Towards AI

JUNE 27, 2023

Offering features like TensorBoard for data visualization and TensorFlow Extended (TFX) for implementing production-ready ML pipelines, TensorFlow stands out as a comprehensive solution for both beginners and seasoned professionals in the realm of machine learning.

Machine Learning 98

Machine Learning Machine Learning ML ML 98

Pickl AI

JULY 23, 2023

Using the right data analytics techniques can help in extracting meaningful insight, and using the same to formulate strategies. The analytics techniques like descriptive analytics, predictive analytics, diagnostic analytics and others find application in diverse industries, including retail, healthcare, finance, and marketing.

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52

Data Science Connect

JULY 24, 2023

By leveraging AI and machine learning algorithms, they can analyze vast amounts of environmental data, weather patterns, and historical records to provide farmers with real-time insights and predictive analytics for informed decision-making.

Data Scientist 130

Data Scientist Internet of Things Predictive Analytics Analytics 130

Ocean Protocol

SEPTEMBER 29, 2023

AI / ML offers tools to give a competitive edge in predictive analytics, business intelligence, and performance metrics. Fantasy Football is a popular pastime for a large amount of the world, we gathered data around the past 6 seasons of player performance data to see what our community of data scientists could create.

Cross Validation 59

Cross Validation Predictive Analytics Exploratory Data Analysis EDA 59

Pickl AI

JUNE 25, 2023

Descriptive Analytics Descriptive analytics focuses on summarizing historical data to gain a better understanding of past events and trends. ” This type of analytics uses various techniques, such as data aggregation, data visualization , and statistical analysis to provide a comprehensive overview of business performance.

Analytics 52

Analytics Analytics Predictive Analytics Machine Learning 52

Towards AI

MARCH 12, 2024

Data analysis: AI tools can analyze vast amounts of data to identify trends, predict customer behavior, and inform strategic decision-making. Task automation: AI automates repetitive tasks like data entry, scheduling, and report generation, freeing your team to focus on higher-level activities.

AI 97

AI AI Predictive Analytics Data Visualization 97

Data Science Blog

FEBRUARY 23, 2023

If you can analyze data with statistical knowledge or unsupervised machine learning, just extracting data without labeling would be enough. And sometimes ad hoc analysis with simple data visualization will help your decision makings. “Shut up and annotate!”

Supervised Learning 264

Supervised Learning Machine Learning Machine Learning Deep Learning 264

Pickl AI

JUNE 4, 2024

Machine learning is used in healthcare to develop predictive models, personalize treatment plans, and automate tasks. Big Data Analytics This involves analyzing massive datasets that are too large and complex for traditional data analysis methods. How Does Data Science Improve Patient Outcomes?

Data Science 52

Data Science Big Data Analytics Big Data Analytics Predictive Analytics 52

Pickl AI

JANUARY 16, 2024

Summary: The blog delves into the 2024 Data Analyst career landscape, focusing on critical skills like Data Visualisation and statistical analysis. It identifies emerging roles, such as AI Ethicist and Healthcare Data Analyst, reflecting the diverse applications of Data Analysis.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Analytics 52

Pickl AI

JANUARY 15, 2025

These tools enable organizations to convert raw data into actionable insights through various means such as reporting, analytics, data visualization, and performance management. Data Processing: Cleaning and organizing data for analysis. How Do I Choose the Right BI Tool for My Organization?

Business Intelligence 52

Business Intelligence Business Intelligence Power BI Data Visualization 52

Pickl AI

JULY 3, 2023

It is the process of converting raw data into relevant and practical knowledge to help evaluate the performance of businesses, discover trends, and make well-informed choices. Data gathering, data integration, data modelling, analysis of information, and data visualization are all part of intelligence for businesses.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

Pickl AI

FEBRUARY 4, 2024

Alteryx’s Capabilities Data Blending: Effortlessly combine data from multiple sources. Predictive Analytics: Leverage machine learning algorithms for accurate predictions. Reporting and Visualization: Craft interactive dashboards and reports seamlessly. Is Alteryx similar to Tableau?

Data Preparation 52

Data Preparation Tableau Data Visualization Analytics 52

Pickl AI

JUNE 12, 2023

How Professionals Can Use Tableau for Data Science? Tableau is a powerful data visualization and business intelligence tool that can be effectively used by professionals in the field of data science. You can further, use Tableau’s drag-and-drop functionality to create insightful visualizations.

Tableau 52

Tableau Data Science Data Scientist Data Analysis 52

Pickl AI

NOVEMBER 2, 2023

A cheat sheet for Data Scientists is a concise reference guide, summarizing key concepts, formulas, and best practices in Data Analysis, statistics, and Machine Learning. It serves as a handy quick-reference tool to assist data professionals in their work, aiding in data interpretation, modeling , and decision-making processes.

Data Scientist 52

Data Scientist Data Science Data Visualization Machine Learning 52

IBM Journey to AI blog

DECEMBER 20, 2023

For instance, if data scientists were building a model for tornado forecasting, the input variables might include date, location, temperature, wind flow patterns and more, and the output would be the actual tornado activity recorded for those days. temperature, salary).

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

ODSC - Open Data Science

AUGUST 21, 2023

Data Visualization and Data Analysis Join some of the world’s most creative minds that are changing the way we visualize, understand, and interact with data. You’ll also learn the art of storytelling, information communication, and data visualization using the latest open-source tools and techniques.

Data Science 52

Data Science Machine Learning Machine Learning Deep Learning 52

Pickl AI

DECEMBER 4, 2023

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Key Components of Data Intelligence In Data Intelligence, understanding its core components is like deciphering the secret language of information.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

Pickl AI

SEPTEMBER 24, 2024

Read More: Use of AI and Big Data Analytics to Manage Pandemics Overview of Uber’s Data Analytics Strategy Uber’s Data Analytics strategy is multifaceted, focusing on real-time data collection, predictive analytics, and Machine Learning.

Analytics 52

Analytics Analytics Machine Learning Machine Learning 52

ODSC - Open Data Science

MARCH 11, 2024

Data Visualization and Data Analysis Join some of the world’s most creative minds that are changing the way we visualize, understand, and interact with data. You’ll also learn the art of storytelling, information communication, and data visualization using the latest open-source tools and techniques.

Data Science 52

Data Science Deep Learning Deep Learning Machine Learning 52

IBM Journey to AI blog

JULY 6, 2023

Machine learning can then “learn” from the data to create insights that improve performance or inform predictions. Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

JANUARY 28, 2025

Effective data modeling enhances the usability of the BI system by making it easier to navigate through complex datasets. Data Analysis At this stage, organizations use various analytical techniques to derive insights from the stored data: Descriptive Analytics: Provides insights into past performance by summarizing historical data.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Pickl AI

OCTOBER 3, 2024

They can automate various aspects of the research process, including: Data Collection AI tools can gather data from multiple sources such as academic journals, databases, and online repositories. This automation reduces the time researchers spend on manual data collection. What type of data do you work with?

AI 52

AI AI Natural Language Processing Machine Learning 52

phData

SEPTEMBER 4, 2024

Insights are immediately generated by entering a data question into ThoughtSpot’s Ask any data question search bar. Data Visualizations ThoughSpot enables users to easily pin data answers and insights to a Liveboard, the ThoughtSpot term for a dashboard. Why Use ThoughtSpot?

Analytics 52

Analytics Analytics SQL ETL 52

Pickl AI

JULY 20, 2023

Descriptive Analytics Projects: These projects focus on summarizing historical data to gain insights into past trends and patterns. Examples include generating reports, dashboards, and data visualizations to understand business performance, customer behavior, or operational efficiency.

Analytics 40

Analytics Analytics Big Data Big Data 40

Data Science Blog

JULY 23, 2023

Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. A Data Product can take various forms, depending on the domain’s requirements and the data it manages.

Data Science 246

Data Science Azure Power BI Business Intelligence 246

Smart Data Collective

OCTOBER 25, 2023

Well, it is – to the ones that are 100% familiar with it – and it involves the use of various data sources, including internal data from company databases, as well as external data, to generate insights, identify trends, and support strategic planning. In the 1990s, OLAP tools allowed multidimensional data analysis.

Business Intelligence 122

Business Intelligence Business Intelligence Analytics Analytics 122

Pickl AI

JUNE 18, 2024

Summary: This blog dives into the most promising Power BI projects, exploring advanced data visualization, AI integration, IoT & blockchain analytics, and emerging technologies. Discover best practices for successful implementation and propel your organization towards data-driven success.

Power BI 52

Power BI Data Analysis Data Analysis Data Visualization 52

IBM Journey to AI blog

JUNE 5, 2024

App cost and revenue analytics, which track app revenue—such as annual recurring revenue and customer lifetime value (the total profit a business can expect to make from a single customer for the duration the business relationship)—and expenditures such as customer acquisition cost (the costs associated with acquiring a new customer).

Analytics 94

Analytics Analytics AI AI 94

Pickl AI

DECEMBER 4, 2024

A key aspect of this evolution is the increased adoption of cloud computing, which allows businesses to store and process vast amounts of data efficiently. According to recent statistics, 56% of healthcare organisations have adopted predictive analytics to improve patient outcomes.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

APRIL 2, 2024

There are three main types, each serving a distinct purpose: Descriptive Analytics (Business Intelligence): This focuses on understanding what happened. Think of it as summarizing past data to answer questions like “Which products are selling best?” ” or “What are our customer demographics?”

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

Dataconomy

MARCH 28, 2025

By leveraging data science and predictive analytics, decision intelligence transforms raw data into actionable insights, fostering a more informed and agile decision-making process. They adopt various techniques to integrate both structured and unstructured data, which is essential for comprehensive analysis.

Data Science 91

Data Science Machine Learning Machine Learning Business Intelligence 91

Dataconomy

MARCH 7, 2025

Salesforce Einstein Built into Salesforces CRM ecosystem , Einstein AI offers predictive analytics, automated insights, and personalized recommendations. Sales teams can forecast trends, optimize lead scoring, and enhance customer engagement all while reducing manual data analysis.

AI 91

AI AI Machine Learning Machine Learning 91

Dataconomy

MARCH 19, 2025

This helps facilitate data-driven decision-making for businesses, enabling them to operate more efficiently and identify new opportunities. Definition and significance of data science The significance of data science cannot be overstated. Machine learning engineer: Focuses on the development of predictive models.

Data Science 91

Data Science Citizen Data Scientist Data Scientist Machine Learning 91