Flipboard

MARCH 8, 2023

ChatGPT for Data Science Cheat Sheet • Top Free Data Science Online Courses for 2023 • SQL Query Optimization Techniques • 3 Hard Python Coding Interview Questions For Data Science • A List of 7 Best Data Modeling Tools for 2023

Data Science 122

Data Science SQL Python Data Models 122

Data Science Dojo

JULY 12, 2023

Welcome to the world of databases, where the choice between SQL (Structured Query Language) and NoSQL (Not Only SQL) databases can be a significant decision. In this blog, we’ll explore the defining traits, benefits, use cases, and key factors to consider when choosing between SQL and NoSQL databases.

SQL 195

SQL Database Big Data Big Data 195

Data Science Dojo

MARCH 8, 2024

Moreover, organized storage of data facilitates data analysis, enabling retrieval of useful insights and data patterns. It also facilitates integration with different applications to enhance their functionality with organized access to data. Data is contained in tables divided into rows and columns.

Database 370

Database Natural Language Processing Clustering SQL 370

Data Science Blog

NOVEMBER 15, 2023

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg.

Data Modeling 245

Data Modeling Data Models Business Intelligence Business Intelligence 245

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. Data scientists use algorithms for creating data models.

Data Science 133

Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

Data Science Blog

SEPTEMBER 19, 2023

In the contemporary age of Big Data, Data Warehouse Systems and Data Science Analytics Infrastructures have become an essential component for organizations to store, analyze, and make data-driven decisions. So why using IaC for Cloud Data Infrastructures?

Data Warehouse 259

Data Warehouse Azure SQL Database 259

Data Science Dojo

MARCH 7, 2023

As data science evolves and grows, the demand for skilled data scientists is also rising. A data scientist’s role is to extract insights and knowledge from data and to use this information to inform decisions and drive business growth.

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? Finally, SQL’s window function. Let’s briefly dive into each bit.

SQL 98

SQL Data Scientist Database Data Science 98

IBM Journey to AI blog

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 94

Data Science Analytics Analytics Data Scientist 94

Data Science Connect

JANUARY 27, 2023

In this blog post, we will be discussing 7 tips that will help you become a successful data engineer and take your career to the next level. Learn SQL: As a data engineer, you will be working with large amounts of data, and SQL is the most commonly used language for interacting with databases.

Data Engineer 130

Data Engineer Data Engineering Data Engineering Data Engineering 130

Dataversity

JANUARY 18, 2021

So, I had to cut down my January 2021 list of things of importance in Data Modeling in this new, fine year (I hope)! The post 2021: Three Game-Changing Data Modeling Perspectives appeared first on DATAVERSITY. Common wisdom has it that we humans can only focus on three things at a time.

Data Models 98

Data Models Data Modeling Database SQL 98

Data Science Dojo

FEBRUARY 9, 2023

They process and analyze large sets of data to identify trends, patterns, and insights that can help organizations make more informed decisions. Uses of Power BI for a Data Analyst – Data Science Dojo Who is a data analyst? Check out this course and learn Power BI today!

Power BI 221

Power BI Data Analyst Data Visualization Data Analysis 221

IBM Journey to AI blog

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? This post will dive deeper into the nuances of each field.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Towards AI

JANUARY 11, 2024

Exploring the way to perform tabular data science activity with LLMImage developed by DALL.E Large Language Models have been rising recently and will be like that in the upcoming year. Tabular data is the data in the typical table — some columns and rows are structured well, like in Excel or SQL data.

Python 126

Python Clean Data Data Science SQL 126

Pickl AI

JUNE 28, 2023

Data is driving most business decisions. In this, data modeling tools play a crucial role in developing and maintaining the information system. Moreover, it involves the creation of a conceptual representation of data and its relationship. Data modeling tools play a significant role in this.

Data Models 52

Data Models Data Modeling Database SQL 52

Data Science Dojo

APRIL 18, 2023

Effective data visualization allows stakeholders to quickly understand complex data and draw actionable insights from it. Programming Programming is a crucial skill for data analysts. Data analysts should be able to manipulate data using programming constructs such as loops, conditional statements, and functions.

Data Analyst 195

Data Analyst Data Visualization Data Analysis Data Analysis 195

Pickl AI

JUNE 12, 2023

Tableau can help Data Scientists generate graphs, charts, maps and data-driven stories, etc for purpose of visualisation and analysing data. But What is Tableau for Data Science and what are its advantages and disadvantages? How Professionals Can Use Tableau for Data Science? Additionally.

Tableau 52

Tableau Data Science Data Scientist Data Analysis 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. Role of Data Scientists Data Scientists are the architects of data analysis.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

DataRobot

FEBRUARY 22, 2021

DataRobot is excited to announce the graduation of the first class of our 10X Applied Data Science Academy. The founding of the 10X Academy is part of DataRobot’s commitment to developing automation that improves the productivity of data scientists while democratizing access to AI for non-data scientists.

Data Science 52

Data Science Data Scientist Citizen Data Scientist Data Analyst 52

ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

Azure 52

Azure ML ML Data Models 52

phData

SEPTEMBER 19, 2023

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Data modeling plays a pivotal role in defining the structure, relationships, and semantics of data within a data lake. Consistency of data throughout the data lake.

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

Smart Data Collective

JUNE 16, 2022

Data science is both a rewarding and challenging profession. One study found that 44% of companies that hire data scientists say the departments are seriously understaffed. Fortunately, data scientists can make due with fewer staff if they use their resources more efficiently, which involves leveraging the right tools.

Analytics 139

Analytics Analytics Data Scientist Data Warehouse 139

Data Science Dojo

JULY 6, 2023

It allows data engineers to build, test, and maintain data pipelines in a version-controlled manner. dbt focuses on transforming raw data into analytics-ready tables using SQL-based transformations.

Data Engineering 195

Data Engineering Data Engineering Data Engineer Data Engineering 195

Dataconomy

OCTOBER 15, 2024

I’ve found that while calculating automation benefits like time savings is relatively straightforward, users struggle to estimate the value of insights, especially when dealing with previously unavailable data. We were developing a data model to provide deeper insights into logistics contracts.

Data Models 113

Data Models Data Modeling Analytics Analytics 113

Mlearning.ai

APRIL 29, 2023

This case study as we’ve mentioned above is all about calculating metrics, and growth and helping the business analyze their data in a smart way to better forecast and plan for their future developments! 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

DagsHub

DECEMBER 11, 2023

The following points illustrates some of the main reasons why data versioning is crucial to the success of any data science and machine learning project: Storage space One of the reasons of versioning data is to be able to keep track of multiple versions of the same data which obviously need to be stored as well.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Data Science 98

AWS Machine Learning Blog

SEPTEMBER 18, 2024

Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly. It promotes a disciplined approach to data modeling, making it easier to ensure data quality and consistency across the ML pipelines. Matúš Chládek is a Senior Engineering Manager for ML Ops at Zeta Global.

AWS 127

AWS Machine Learning Machine Learning ML 127

ODSC - Open Data Science

SEPTEMBER 27, 2023

In contrast, data warehouses and relational databases adhere to the ‘Schema-on-Write’ model, where data must be structured and conform to predefined schemas before being loaded into the database. This ensures data consistency and integrity. You can connect with her on Linkedin.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. No-code/low-code experience using a diagram view in the data preparation layer similar to Dataflows.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

Dataconomy

MAY 2, 2023

Machine learning engineers are professionals who possess a blend of skills in software engineering and data science. Their primary role is to leverage their programming and coding abilities to gather, process, and analyze large volumes of data. Does a machine learning engineer do coding? percentage points.

ML 110

ML ML Machine Learning Machine Learning 110

phData

SEPTEMBER 26, 2023

Data flows from the current data platform to the destination. The necessary access is granted so data flows without issue. SQL Server Agent jobs). Either way, it’s important to understand what data is transformed, and how so. Reporting The goal of this exercise is to determine how data is consumed.

SQL 52

SQL Database ETL Data Models 52

Pickl AI

MAY 30, 2023

For instance, Data Science Course with Placement Guarantee is one of the most in-demand courses that aspirants are looking for. Instances of Professionals courses include Data Science Bootcamp Job Guarantee, Python for Data Science, Data Analytics, Business Analytics, etc.

Data Science 52

Data Science Data Mining Data Mining Data Mining 52

Pickl AI

OCTOBER 16, 2024

Summary: Relational Database Management Systems (RDBMS) are the backbone of structured data management, organising information in tables and ensuring data integrity. This article explores RDBMS’s features, advantages, applications across industries, the role of SQL, and emerging trends shaping the future of data management.

Database 52

Database SQL Analytics Analytics 52

The MLOps Blog

JUNE 27, 2023

Google Cloud Vertex AI Google Cloud Vertex AI provides a unified environment for both automated model development with AutoML and custom model training using popular frameworks. Qwak Qwak is a fully-managed, accessible, and reliable ML platform to develop and deploy models and monitor the entire machine learning pipeline.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

ODSC - Open Data Science

FEBRUARY 14, 2023

The database would need to be highly available and resilient, with features like automatic failover and data replication to ensure that the system remains up and running even in the face of hardware or software failures. This could be achieved through the use of a NoSQL data model, such as document or key-value stores.

Database 124

Database AI AI Natural Language Processing 124

Women in Big Data

DECEMBER 9, 2024

Lookers strength lies in its ability to connect to a wide variety of data sources. Examples include SQl, DWH, and Cloud based systems (Google Bigquery). With Looker, you can share dashboards and visualizations seamlessly across teams, providing stakeholders with access to real-time data.

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Big Data Big Data Power BI Tableau 52