Data Science Dojo

OCTOBER 4, 2024

Key Skills Required Knowledge of Algorithms and Predictive Models: Proficiency in using algorithms and predictive models to forecast future trends based on present data. Data Visualization Techniques: Ability to transform complex data into understandable graphs and charts.

Computer Science 409

Computer Science Computer Science Database Administration Data Scientist 409

Data Science Dojo

FEBRUARY 9, 2023

Data is an essential component of any business, and it is the role of a data analyst to make sense of it all. Power BI is a powerful data visualization tool that helps them turn raw data into meaningful insights and actionable decisions. Learn Power BI with this crash course in no time!

Power BI 221

Power BI Data Analyst Data Visualization Data Analysis 221

Data Science Dojo

MAY 1, 2023

Pandas Pandas is a powerful data manipulation library for Python that provides fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data easy and intuitive.

Python 239

Python Machine Learning Machine Learning Data Science 239

Data Science Dojo

MARCH 7, 2023

These skills include programming languages such as Python and R, statistics and probability, machine learning, data visualization, and data modeling. Data preparation is an essential step in the data science workflow, and data scientists should be familiar with various data preparation tools and best practices.

Data Scientist 221

Data Scientist Exploratory Data Analysis Data Science Data Visualization 221

ODSC - Open Data Science

APRIL 6, 2023

Though both are great to learn, what gets left out of the conversation is a simple yet powerful programming language that everyone in the data science world can agree on, SQL. But why is SQL, or Structured Query Language , so important to learn? Let’s start with the first clause often learned by new SQL users, the WHERE clause.

SQL 98

SQL Data Scientist Database Data Science 98

Data Science Dojo

MAY 18, 2023

Data Storytelling in Action: This panel will discuss the importance of data visualization in storytelling in different industries, different visualization tools, tips on improving one’s visualization skills, personal experiences, breakthroughs, pressures, and frustrations as well as successes and failures.

Data Science 195

Data Science AI AI SQL 195

Data Science Dojo

JULY 3, 2024

Data science bootcamps are intensive short-term educational programs designed to equip individuals with the skills needed to enter or advance in the field of data science. They cover a wide range of topics, ranging from Python, R, and statistics to machine learning and data visualization.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Smart Data Collective

SEPTEMBER 21, 2020

The first step in understanding COVID-19 infection is the most straightforward: figure out where and how infections are spreading and, to this end, graph databases have been a particularly powerful tool. Another insight from graphing and modeling COVID databases?

Big Data 143

Big Data Big Data Database SQL 143

ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. Data visualization can help here by visualizing your datasets.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

ODSC - Open Data Science

NOVEMBER 3, 2023

Data visualization tools turn insights and data into something understandable, especially for non-data stakeholders who may not share the same skillsets as the team who’s behind the data. So let’s take a look at seven trending data visualization tools that have gotten quite a bit of attention on GitHub this year.

Data Visualization 52

Data Visualization Python SQL Database 52

Dataconomy

JULY 24, 2023

You might be asking, “How to become a data scientist with a background in a different field?” ” Data management and manipulation Data scientists often deal with vast amounts of data, so it’s crucial to understand databases, data architecture, and query languages like SQL.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

AWS Machine Learning Blog

DECEMBER 11, 2024

By moving our core infrastructure to Amazon Q, we no longer needed to choose a large language model (LLM) and optimize our use of it, manage Amazon Bedrock agents, a vector database and semantic search implementation, or custom pipelines for data ingestion and management. Jonathan Garcia is a Sr.

AWS 91

AWS Database AI AI 91

Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. If it’s not done right away, then later.

Database 130

Database Data Visualization Big Data Big Data 130

Pickl AI

APRIL 3, 2025

Summary: Data Analysis focuses on extracting meaningful insights from raw data using statistical and analytical methods, while data visualization transforms these insights into visual formats like graphs and charts for better comprehension. Deep Dive: What is Data Visualization?

Data Analysis 52

Data Analysis Data Analysis Data Visualization EDA 52

Cambridge Intelligence

OCTOBER 25, 2023

Visualizing graph data doesn’t necessarily depend on a graph database… Working on a graph visualization project? You might assume that graph databases are the way to go – they have the word “graph” in them, after all. Do I need a graph database? It depends on your project. Unstructured?

Database 64

Database Data Modeling Data Models Algorithm 64

Cambridge Intelligence

OCTOBER 19, 2023

That’s why our data visualization SDKs are database agnostic: so you’re free to choose the right stack for your application. There have been a lot of new entrants and innovations in the graph database category, with some vendors slowly dipping below the radar, or always staying on the periphery.

Database 59

Database Azure SQL Analytics 59

Pickl AI

JULY 3, 2024

Summary: Master SQL ranking functions to analyze data order and uncover trends. Introduction to SQL Ranking In the realm of Data Analysis, extracting insights often goes beyond simple aggregations. Introduction to SQL Ranking In the realm of Data Analysis, extracting insights often goes beyond simple aggregations.

SQL 52

SQL Data Analysis Data Analysis Database 52

Smart Data Collective

OCTOBER 14, 2019

They would source large volumes of data from different platforms into Hadoop’s. NoSQL and SQL. In addressing storage needs, traditional databases like Oracle are being replaced. Developers need an understanding of MongoDB, Couchbase, and other NoSQL database types. Apache Spark. Quantitative Analysis.

Big Data 99

Big Data Big Data Apache Hadoop Hadoop 99

Dataconomy

JUNE 1, 2023

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. OneLake is designed to store a single copy of data in a unified location, leveraging the open-source Apache Parquet format.

Power BI 194

Power BI Data Lakes Azure Data Silos 194

Mlearning.ai

FEBRUARY 13, 2023

Welcome to the wild, wacky world of databases! to the digital world, you’ll find that these unsung heroes of the digital age are essential for keeping your data organised and secure. But with so many types of databases to choose from, how do you know which one is right for you? The most well-known graph database is Neo4j.

Database 52

Database Data Modeling Data Models Big Data 52

ODSC - Open Data Science

FEBRUARY 13, 2025

Build a Data Analyst AI Agent fromScratch Daniel Herrera, Principal Developer Advocate atTeradata Daniel Herrera guided attendees through the process of building a data analyst AI agent from the ground up. He covered schema design, vector indexing, and ranking functions to optimize AI-driven search and recommendation systems.

AI 52

AI AI Data Analyst Database 52

Pickl AI

MARCH 3, 2025

Summary: Business Intelligence Analysts transform raw data into actionable insights. They use tools and techniques to analyse data, create reports, and support strategic decisions. Key skills include SQL, data visualization, and business acumen. Introduction We are living in an era defined by data.

Business Intelligence 52

Business Intelligence Business Intelligence Data Analyst Data Visualization 52

Smart Data Collective

AUGUST 10, 2021

It can connect any data source, although the better your source, the better the results will be. Another key benefit is that it allows companies to create data visualizations! Another cloud-based software with an easy-to-use interface, Looker provides not only data analytics and management, but also business intelligence tools.

Analytics 132

Analytics Analytics Data Science Tableau 132

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

JULY 18, 2023

It is popular for its powerful data visualization and analysis capabilities. Hence, Data Scientists rely on R to perform complex statistical operations. With a wide array of packages like ggplot2 and dplyr, R allows for sophisticated data visualization and efficient data manipulation. Wrapping it up !!!

Data Science 52

Data Science SQL Data Scientist Python 52

Analytics Vidhya

DECEMBER 27, 2022

This article was published as a part of the Data Science Blogathon. Source: Author(Paint) Introduction Arushi is a data architect in a company named Redeem. The company provides cashback to customers who check in at restaurants & hotels.

Data Science 306

Data Science Analytics Analytics Data Visualization 306

Tableau

OCTOBER 8, 2021

With Looker’s secure, trusted and highly performant data governance capabilities, we can augment Tableau’s world-class data visualization capabilities to enable data-driven decisions across the enterprise. Tableau Prep allows you to combine, reshape, and clean data using an easy-to-use, visual, and direct interface.

Tableau 138

Tableau Analytics Analytics Machine Learning 138

ODSC - Open Data Science

FEBRUARY 8, 2023

Common databases appear unable to cope with the immense increase in data volumes. This is where the BigQuery data warehouse comes into play. BigQuery operation principles Business intelligence projects presume collecting information from different sources into one database. BigQuery for Marketing: What Makes it Special?

Database 97

Database Data Science Big Data Big Data 97

Pickl AI

AUGUST 15, 2023

Coding Skills for Data Analytics Coding is an essential skill for Data Analysts, as it enables them to manipulate, clean, and analyze data efficiently. Programming languages such as Python, R, SQL, and others are widely used in Data Analytics. Ideal for academic and research-oriented Data Analysis.

Analytics 52

Analytics Analytics Data Analyst Data Analysis 52

Mlearning.ai

APRIL 29, 2023

Available Data The Data Bank team has prepared a data model for this case study as well as a few example rows from the complete dataset below to get you familiar with their tables. Submission Suggestions 8-Week SQL Challenge: Data Bank was originally published in MLearning.ai BECOME a WRITER at MLearning.ai

SQL 52

SQL Power BI Cloud Data Data Analysis 52

IBM Journey to AI blog

MAY 12, 2023

The dashboard aims to provide easy-to-understand data visualizations, report preparation and baseline accounting of their cloud-usage-based greenhouse gas emissions.

Azure 93

Azure Database Data Visualization Clustering 93

ODSC - Open Data Science

MARCH 2, 2023

Improving your data literacy not only involves hard skills, such as programming languages, but soft skills such as interpersonal communication, and stakeholder relations, as well as blended skills such as data visualization. SQL Databases might sound scary, but honestly, they’re not all that bad.

Data Science 52

Data Science SQL Deep Learning Deep Learning 52

ODSC - Open Data Science

APRIL 3, 2023

As you’ll see below, however, a growing number of data analytics platforms, skills, and frameworks have altered the traditional view of what a data analyst is. Data Presentation: Communication Skills, Data Visualization Any good data analyst can go beyond just number crunching.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

phData

AUGUST 25, 2023

The migration of SSRS (SQL Server Reporting Services) reports to Power BI Service marks a significant shift in data visualization and reporting capabilities. During the migration process, existing.rdl reports are pointed to a Snowflake Data Cloud database from an existing data source in Power BI Report Builder.

Power BI 52

Power BI SQL Data Governance Database 52

Data Science 101

JUNE 10, 2019

Data Engineers. Data engineers typically handle large amounts of data and lay the groundwork for data scientists to do their jobs effectively. They are responsible for managing database systems, scaling data architecture to multiple servers, and writing complex queries to sift through the data.

Data Science 96

Data Science Data Scientist Data Analyst Data Engineering 96