ODSC - Open Data Science

FEBRUARY 8, 2023

Big Data here is a fundamental part of the scenario as it enables the technical integration of data from all digital environments along the customer path. BigQuery operation principles Business intelligence projects presume collecting information from different sources into one database.

Big Data 97

Big Data Business Intelligence Data Mining Data Science 97

Marktechpost

JUNE 29, 2023

The top business intelligence solutions make finding insights into data and effectively communicating them to stakeholders easier. However, most of this information is siloed and can only be put together with the help of specialized business intelligence (BI) tools.

Business Intelligence 94

Business Intelligence Machine Learning Data Analysis Natural Language Processing 94

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 Analysis 52

Data Analysis Data Scientist Data Science Machine Learning 52

Pickl AI

APRIL 26, 2024

Top 50+ Interview Questions for Data Analysts Technical Questions SQL Queries What is SQL, and why is it necessary for data analysis? SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. How would you segment customers based on their purchasing behaviour?

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

Pickl AI

JULY 18, 2023

While it may not be a traditional programming language, SQL plays a crucial role in Data Science by enabling efficient querying and extraction of data from databases. SQL’s powerful functionalities help in extracting and transforming data from various sources, thus helping in accurate data analysis.

Data Science 52

Data Science Data Scientist Python Business Intelligence 52

Pickl AI

FEBRUARY 28, 2023

However, Data Scientists use tools like Python, Java, and Machine Learning for manipulating and analysing data. Significantly, in contrast, Data Analysts utilise their proficiency in a relational databases, Business Intelligence programs and statistical software.

Data Scientist 52

Data Scientist Data Mining Data Science Machine Learning 52

IBM Journey to AI blog

AUGUST 28, 2023

As it pertains to social media data, text mining algorithms (and by extension, text analysis) allow businesses to extract, analyze and interpret linguistic data from comments, posts, customer reviews and other text on social media platforms and leverage those data sources to improve products, services and processes.

Convolutional Neural Networks 144

Convolutional Neural Networks Data Mining Categorization Machine Learning 144

Pickl AI

MARCH 16, 2023

For this, you should open the Symbol dialogue box: Excel: Insert > Symbols Also Read: Use of Excel in Data Analysis What Are The Benefits of Using Shortcut Excel Keys? Most of the in-demand technologies like data science, blockchain, big data, and artificial intelligence have some role in Excel.

Data Science 52

Data Science Big Data Data Analysis Artificial Intelligence 52

Viso.ai

NOVEMBER 19, 2023

It is useful for various tasks related to machine learning, deep learning, data management, Natural Language Processing (NLP) , etc. Infosys Nia provides companies with the opportunity to leverage AI on existing big data, by automating repetitive tasks and scheduled responsibilities. You can schedule a demo with an Observe.AI

Computer Vision 97

Computer Vision Natural Language Processing Machine Learning Deep Learning 97

Unite.AI

DECEMBER 5, 2023

In this digital economy, data is paramount. Today, all sectors, from private enterprises to public entities, use big data to make critical business decisions. However, the data ecosystem faces numerous challenges regarding large data volume, variety, and velocity. Enter data warehousing!

Metadata 162

Metadata Big Data ETL Data Ingestion 162

Pickl AI

NOVEMBER 15, 2023

Data scientists can explore, experiment, and derive valuable insights without the constraints of a predefined structure. This capability empowers organizations to uncover hidden patterns, trends, and correlations in their data, leading to more informed decision-making. It often serves as a source for Data Warehouses.

ETL 52

ETL Metadata Business Intelligence Data Analysis 52

Marktechpost

JULY 23, 2023

A data warehouse is a data management system for data reporting, analysis, and storage. It is an enterprise data warehouse and is part of business intelligence. Data from one or more diverse sources is stored in data warehouses, which are central repositories.

Machine Learning 52

Machine Learning ETL Big Data Data Integration 52

Artificial Corner

JUNE 6, 2023

Timeline of data engineering — Created by the author using canva In this post, I will cover everything from the early days of data storage and relational databases to the emergence of big data, NoSQL databases, and distributed computing frameworks.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

ODSC - Open Data Science

JUNE 2, 2023

Augmented Analytics — Where Do You Fit in at the Intersection of Analytics and Business Intelligence? Data visualization is a critical way for anyone to turn endless rows of data into easy-to-understand results through dynamic and understandable visuals. Win-win, right? So where do you fit into the BI equation?

Business Intelligence 52

Business Intelligence Automation Composite AI Data Discovery 52

Artificial Corner

JUNE 6, 2023

With a single shake of their staff they can command the power of data into magical intelligence never seen before, intelligence that will finally provide the answer to the unanswerable. Big tech have been shedding staff in a bid to adjust to the current volatile economic environment. This will impact the data realm.

Big Data 52

Big Data Data Mining Data Scientist Business Intelligence 52

O'Reilly Media

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Algorithm 99

Algorithm Machine Learning Neural Network Data Scientist 99

Pickl AI

JANUARY 25, 2023

The requirement of SQL in Data Science is to conduct analytical performances on data that are stored in relational databases. While using Big Data Tools, Data Scientists need SQL which helps them in Data Wrangling and preparation. Based on the type of analysis, the SQL Join is performed.

Data Science 52

Data Science Data Analysis Data Scientist Big Data 52

Pickl AI

JUNE 12, 2023

A Data Scientist requires to be able to visualize quickly the data before creating the model and Tableau is helpful for that. Tableau further has its own drawbacks in case of its use in Data Science considering it is a Data Analysis tool rather than a tool for Data Science.

Data Science 52

Data Science Data Scientist Data Analysis Machine Learning 52

Marktechpost

JULY 17, 2023

It is a clear leader in all types of analytics tools and methodologies, including predictive analytics, and has continued to invent new tools used by statisticians and data scientists. government launched the first version of the company’s tools to better data analysis for healthcare in 1966.

Machine Learning 93

Machine Learning Data Mining Data Scientist Artificial Intelligence 93

AWS Machine Learning Blog

MAY 10, 2023

Business analysts play a pivotal role in facilitating data-driven business decisions through activities such as the visualization of business metrics and the prediction of future events. Then they can create predictive dashboards with the data. Let’s create a visual to show the count by loan status.

ML 75

ML Data Analysis Machine Learning Metadata 75

Mlearning.ai

MAY 23, 2023

In the final stage, the results are communicated to the business in a visually appealing manner. This is where the skill of data visualization, reporting, and different business intelligence tools come into the picture. What is the difference between data analytics and data science?

Data Science 52

Data Science Neural Network Deep Learning Machine Learning 52

Pickl AI

APRIL 2, 2024

The Three Types of Data Science Data science isn’t a one-size-fits-all solution. There are three main types, each serving a distinct purpose: Descriptive Analytics (Business Intelligence): This focuses on understanding what happened. Hadoop/Spark: Frameworks for distributed storage and processing of big data.

Data Science 52

Data Science Data Scientist Machine Learning Big Data 52