Analytics Vidhya

MARCH 8, 2023

The Biggest Data Science Blogathon is now live! Knowledge is power. Sharing knowledge is the key to unlocking that power.”― Martin Uzochukwu Ugwu Analytics Vidhya is back with the largest data-sharing knowledge competition- The Data Science Blogathon.

Data Science 345

Data Science Analytics Analytics Apache Hadoop 345

Smart Data Collective

NOVEMBER 8, 2020

As such, you should begin by learning the basics of SQL. SQL is an established language used widely in data engineering. Just like programming, SQL has multiple dialects. Besides SQL, you should also learn how to model data. As a data engineer, you will be primarily working on databases.

Data Engineer 104

Data Engineer Data Engineering Data Engineering Data Engineering 104

Pickl AI

DECEMBER 25, 2024

Descriptive analytics is a fundamental method that summarizes past data using tools like Excel or SQL to generate reports. Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently. Data Analysts dive deeper into raw data, using tools like Excel, Tableau, and SQL to create reports and dashboards.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

O'Reilly Media

SEPTEMBER 15, 2021

Cloud certifications, specifically in AWS and Microsoft Azure, were most strongly associated with salary increases. As we’ll see later, cloud certifications (specifically in AWS and Microsoft Azure) were the most popular and appeared to have the largest effect on salaries. Many respondents acquired certifications. What about Kafka?

AI 145

AI AI Azure AWS 145

Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Databases and SQL : Managing and querying relational databases using SQL, as well as working with NoSQL databases like MongoDB.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Analytics Vidhya

JANUARY 8, 2023

Hey, are you the data science geek who spends hours coding, learning a new language, or just exploring new avenues of data science? If all of these describe you, then this Blogathon announcement is for you! Analytics Vidhya is back with its 28th Edition of blogathon, a place where you can share your knowledge about […].

Data Science 328

Data Science Analytics Analytics Hadoop 328

phData

NOVEMBER 8, 2024

Cost Efficiency and Scalability Open Table Formats are designed to work with cloud storage solutions like Amazon S3, Google Cloud Storage, and Azure Blob Storage, enabling cost-effective and scalable storage solutions. Amazon S3, Azure Data Lake, or Google Cloud Storage).

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Big Data Technologies: Hadoop, Spark, etc. Cloud Platforms: AWS, Azure, Google Cloud, etc.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

NOVEMBER 4, 2024

Various types of storage options are available, including: Relational Databases: These databases use Structured Query Language (SQL) for data management and are ideal for handling structured data with well-defined relationships. Apache Spark Spark is a fast, open-source data processing engine that works well with Hadoop.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Mlearning.ai

MAY 23, 2023

Familiarity with libraries like pandas, NumPy, and SQL for data handling is important. Check out this course to upskill on Apache Spark —  [link] Cloud Computing technologies such as AWS, GCP, Azure will also be a plus. This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA).

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JANUARY 13, 2025

Proficiency in programming languages like Python and SQL. Key Skills Experience with cloud platforms (AWS, Azure). Familiarity with SQL for database management. Hadoop , Apache Spark ) is beneficial for handling large datasets effectively. Salary Range: 12,00,000 – 35,00,000 per annum.

AI 52

AI AI Machine Learning Machine Learning 52

Pickl AI

JUNE 7, 2024

Key Features Out-of-the-Box Connectors: Includes connectors for databases like Hadoop, CRM systems, XML, JSON, and more. Microsoft SQL Server Integration Services (SSIS) Microsoft SQL Server Integration Services (SSIS) is an enterprise-level platform for data integration and transformation. How to drop a database in SQL server?

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

DagsHub

DECEMBER 11, 2023

Dolt Created in 2019, Dolt is an open-source tool for managing SQL databases that uses version control similar to Git. It versions tables instead of files and has a SQL query interface for those tables. DVC lacks crucial relational database features, making it an unsuitable choice for those familiar with relational databases.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Data Science 98

Pickl AI

NOVEMBER 5, 2024

Its popularity stems from its user-friendly interface and seamless integration with widely used Microsoft applications like Excel and Azure, making it highly accessible for organisations already using Microsoft products. Tableau supports many data sources, including cloud databases, SQL databases, and Big Data platforms.

Power BI 52

Power BI Tableau Business Intelligence Business Intelligence 52

Mlearning.ai

MARCH 15, 2023

Familiarity with Databases; SQL for structured data, and NOSQL for unstructured data. Experience with cloud platforms like; AWS, AZURE, etc. Knowledge of big data platforms like; Hadoop and Apache Spark. Experience with machine learning frameworks for supervised and unsupervised learning.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

IBM Journey to AI blog

JANUARY 18, 2023

This is an architecture that’s well suited for the cloud since AWS S3 or Azure DLS2 can provide the requisite storage. It can include technologies that range from Oracle, Teradata and Apache Hadoop to Snowflake on Azure, RedShift on AWS or MS SQL in the on-premises data center, to name just a few. It can be codified.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Pickl AI

DECEMBER 4, 2024

Grasp the Fundamentals of Data Analysis and Management Build a strong foundation in Data Analysis by learning data manipulation techniques using SQL and Excel. Focus on Python and R for Data Analysis, along with SQL for database management. This foundational knowledge is essential for any Data Science project.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

The MLOps Blog

JANUARY 23, 2023

It supports most major cloud providers, such as AWS, GCP, and Azure. More about Neptune: Working with artifacts: versioning datasets in runs How to version datasets or models stored in the S3 compatible storage Dolt Dolt is a SQL database that is created for versioning and sharing data.

ML 52

ML ML Data Lakes Machine Learning 52

Pickl AI

APRIL 2, 2024

SQL (Structured Query Language): Language for managing and querying relational databases. Hadoop/Spark: Frameworks for distributed storage and processing of big data. Cloud Platforms (AWS, Azure, Google Cloud): Infrastructure for scalable and cost-effective data storage and analysis.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

ODSC - Open Data Science

JANUARY 7, 2025

While knowing Python, R, and SQL is expected, youll need to go beyond that. Similar to previous years, SQL is still the second most popular skill, as its used for many backend processes and core skills in computer science and programming. Employers arent just looking for people who can program.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

DagsHub

OCTOBER 23, 2024

Here’s the structured equivalent of this same data in tabular form: With structured data, you can use query languages like SQL to extract and interpret information. Popular data lake solutions include Amazon S3 , Azure Data Lake , and Hadoop. This text has a lot of information, but it is not structured.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Data Science Blog

MAY 15, 2023

Data Lakehouses werden auf Cloud-basierten Objektspeichern wie Amazon S3 , Google Cloud Storage oder Azure Blob Storage aufgebaut. Data Warehouses wurden entwickelt, um strukturierte Daten aus Transaktionssystemen in einem zentralen Repository zu speichern, wo sie mit SQL-basierten Tools bereinigt, umgewandelt und analysiert werden konnten.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

Pickl AI

FEBRUARY 23, 2025

Best Big Data Tools Popular tools such as Apache Hadoop, Apache Spark, Apache Kafka, and Apache Storm enable businesses to store, process, and analyse data efficiently. Key Features : Scalability : Hadoop can handle petabytes of data by adding more nodes to the cluster. Use Cases : Yahoo!

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52

Pickl AI

MARCH 19, 2025

Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Python, SQL, and Apache Spark are essential for data engineering workflows. SQL Structured Query Language ( SQL ) is a fundamental skill for data engineers.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52