Data Science Dojo

OCTOBER 31, 2024

Strong analytical skills and the ability to work with large datasets are critical, as is familiarity with data modeling and ETL processes. Additionally, knowledge of programming languages like Python or R can be beneficial for advanced analytics. Prepare to discuss your experience and problem-solving abilities with these languages.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

Analytics Vidhya

OCTOBER 12, 2022

Introduction Since the 1970s, relational database management systems have solved the problems of storing and maintaining large volumes of structured data. With the advent of big data, several organizations realized the benefits of big data processing and started choosing solutions like Hadoop to […].

Hadoop 353

Hadoop Big Data Big Data Data Science 353

Analytics Vidhya

AUGUST 17, 2022

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will introduce you to the big data ecosystem and the role of Apache Spark in Big data. We will also cover the Distributed database system, the backbone of big data. In today’s world, data is the fuel.

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Big Data Big Data Data Science Database 302

Analytics Vidhya

FEBRUARY 28, 2023

To achieve maximum efficiency, every company strives to use various data at every stage of its operations.

Data Science 353

Data Science Data Preparation Big Data Big Data 353

Smart Data Collective

OCTOBER 11, 2021

If you enjoy working with data, or if you’re just interested in a career with a lot of potential upward trajectory, you might consider a career as a data engineer. But what exactly does a data engineer do, and how can you begin your career in this niche? What Is a Data Engineer?

Data Engineering 132

Data Engineering Data Engineering Data Engineering Data Engineer 132

Smart Data Collective

OCTOBER 14, 2019

From the tech industry to retail and finance, big data is encompassing the world as we know it. More organizations rely on big data to help with decision making and to analyze and explore future trends. Big Data Skillsets. They’re looking to hire experienced data analysts, data scientists and data engineers.

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Big Data Big Data Apache Hadoop Hadoop 99

Analytics Vidhya

DECEMBER 26, 2022

NoSQL databases are often used for big data and real-time web applications. Introduction A NoSQL database is a non-relational database that does not use the traditional table-based schema of a relational database. The main advantages of using a NoSQL database are that NoSQL […].

Database 289

Database Big Data Big Data Data Science 289

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. using for loops in Python). IaC allows these teams to collaborate more effectively.

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Data Science Dojo

APRIL 27, 2023

This blog lists down-trending data science, analytics, and engineering GitHub repositories that can help you with learning data science to build your own portfolio.  What is GitHub? GitHub is a powerful platform for data scientists, data analysts, data engineers, Python and R developers, and more.

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Data Science Analytics Analytics Power BI 195

How to Learn Machine Learning

APRIL 26, 2025

The field of data science is now one of the most preferred and lucrative career options available in the area of data because of the increasing dependence on data for decision-making in businesses, which makes the demand for data science hires peak.

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Data Science Data Analyst Data Scientist Machine Learning 52

Analytics Vidhya

OCTOBER 4, 2022

It is a Lucene-based search engine developed in Java but supports clients in various languages ​​such as Python, C#, Ruby, and PHP. It takes unstructured data from multiple sources as input and stores it […]. Introduction Elasticsearch is a search platform with quick search capabilities.

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Smart Data Collective

NOVEMBER 8, 2020

Big data is changing the future of almost every industry. The market for big data is expected to reach $23.5 Data science is an increasingly attractive career path for many people. If you want to become a data scientist, then you should start by looking at the career options available. billion by 2025.

Data Engineering 104

Data Engineering Data Engineering Data Engineering Data Engineer 104

Towards AI

FEBRUARY 2, 2024

I hope that you have sufficient knowledge of big data and Hadoop concepts like Map, reduce, transformations, actions, lazy evaluation, and many more topics in Hadoop and Spark. Before starting to do transformations or any data analysis using Pyspark it is important to create a spark session. Let’s get into the context.

Data Engineering 115

Data Engineering Data Engineering Data Engineer Data Engineering 115

Hacker News

JULY 18, 2024

ABOUT EVENTUAL Eventual is a data platform that helps data scientists and engineers build data applications across ETL, analytics and ML/AI. OUR PRODUCT IS OPEN-SOURCE AND USED AT ENTERPRISE SCALE Our distributed data engine Daft [link] is open-sourced and runs on 800k CPU cores daily.

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Pickl AI

AUGUST 1, 2023

Aspiring and experienced Data Engineers alike can benefit from a curated list of books covering essential concepts and practical techniques. These 10 Best Data Engineering Books for beginners encompass a range of topics, from foundational principles to advanced data processing methods. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

APRIL 6, 2023

Accordingly, one of the most demanding roles is that of Azure Data Engineer Jobs that you might be interested in. The following blog will help you know about the Azure Data Engineering Job Description, salary, and certification course. How to Become an Azure Data Engineer?

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Azure Data Engineering Data Engineering Data Engineering 52

Data Science Dojo

JANUARY 10, 2023

All data roles are identical It’s a common data science myth that all data roles are the same. So, let’s distinguish between some common data roles – data engineer, data scientist, and data analyst. This requires significant focus on producing good quality data in the first place.

Data Science 195

Data Science Data Scientist Data Analyst Machine Learning 195

Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Read more to know.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Flipboard

MARCH 7, 2023

This post presents and compares options and recommended practices on how to manage Python packages and virtual environments in Amazon SageMaker Studio notebooks. You can manage app images via the SageMaker console, the AWS SDK for Python (Boto3), and the AWS Command Line Interface (AWS CLI). Define a Dockerfile.

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Python AWS ML ML 123

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 Engineering Data Engineer 52

ODSC - Open Data Science

FEBRUARY 2, 2023

This doesn’t mean anything too complicated, but could range from basic Excel work to more advanced reporting to be used for data visualization later on. Computer Science and Computer Engineering Similar to knowing statistics and math, a data scientist should know the fundamentals of computer science as well.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

ODSC - Open Data Science

MAY 5, 2023

Data science and data engineering are incredibly resource intensive. By using cloud computing, you can easily address a lot of these issues, as many data science cloud options have databases on the cloud that you can access without needing to tinker with your hardware. Delta & Databricks Make This A Reality!

Data Science 52

Data Science Data Engineering Data Engineering Data Engineering 52

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.

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Data Science Machine Learning Machine Learning Data Visualization 150

Dataconomy

JULY 24, 2023

Concepts such as linear algebra, calculus, probability, and statistical theory are the backbone of many data science algorithms and techniques. Programming skills A proficient data scientist should have strong programming skills, typically in Python or R, which are the most commonly used languages in the field.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

Flipboard

DECEMBER 11, 2024

Organizations are building data-driven applications to guide business decisions, improve agility, and drive innovation. Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Choose the plus sign and for Notebook , choose Python 3.

SQL 158

SQL AWS Data Lakes AI 158

ODSC - Open Data Science

MARCH 6, 2023

Primary Coding Language for Machine Learning Likely to the surprise of no one, python by far is the leading programming language for machine learning practitioners. Big data analytics is evergreen, and as more companies use big data it only makes sense that practitioners are interested in analyzing data in-house.

Machine Learning 116

Machine Learning Machine Learning Data Science Deep Learning 116

Pickl AI

DECEMBER 25, 2024

Key Tools and Techniques Data Science relies on a wide array of tools and techniques to process and analyze large datasets. Programming languages like Python and R are commonly used for data manipulation, visualization, and statistical modeling. Data Scientists require a robust technical foundation. Masters or Ph.D.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

phData

SEPTEMBER 20, 2023

Snowpark is the set of libraries and runtimes in Snowflake that securely deploy and process non-SQL code, including Python , Java, and Scala. On the server side, runtimes include Python, Java, and Scala in the warehouse model or Snowpark Container Services (private preview). This can be a major optimization.

SQL 98

SQL Python Data Lakes Machine Learning 98

AWS Machine Learning Blog

SEPTEMBER 3, 2024

Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. However, managing the complex infrastructure required for big data workloads has traditionally been a significant challenge, often requiring specialized expertise.

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AWS Clustering Big Data Big Data 120

Smart Data Collective

FEBRUARY 3, 2022

There are a lot of compelling reasons that Docker is becoming very valuable for data scientists and developers. If you are a Data Scientist or Big Data Engineer, you probably find the Data Science environment configuration painful. Let’s suppose you want to work with Python.

Data Science 133

Data Science Data Scientist Big Data Big Data 133

AWS Machine Learning Blog

FEBRUARY 21, 2025

This setup uses the AWS SDK for Python (Boto3) to interact with AWS services. Rajesh Nedunuri is a Senior Data Engineer within the Amazon Worldwide Returns and ReCommerce Data Services team. He specializes in designing, building, and optimizing large-scale data solutions.

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Analytics Vidhya

SEPTEMBER 15, 2020

Overview Indexing is MongoDB – a key aspect to managing and executing your database queries efficiently in data science Learn how indexing works in. The post Learning Database for Data Science Tutorial – Perform MongoDB Indexing using PyMongo appeared first on Analytics Vidhya.

Data Science 383

Data Science Database Analytics Analytics 383

Analytics Vidhya

OCTOBER 19, 2022

This article was published as a part of the Data Science Blogathon. Introduction Missing data in machine learning is a type of data that contains null values, whereas Sparse data is a type of data that does not contain the actual values of features; it is a dataset containing a high amount of zero or […].

Machine Learning 381

Machine Learning Machine Learning Data Science Analytics 381

Analytics Vidhya

NOVEMBER 1, 2022

This article was published as a part of the Data Science Blogathon. Sometimes even after successfully loading and reading data, you run out of memory amid data processing operations! Introduction Have you ever encountered an “out-of-memory” error while working on a dataset? It’s pretty frustrating, right?

Data Science 381

Data Science Analytics Analytics Data Engineering 381

Analytics Vidhya

NOVEMBER 18, 2019

Overview Here’s a quick introduction to building machine learning pipelines using PySpark The ability to build these machine learning pipelines is a must-have skill. The post Want to Build Machine Learning Pipelines? A Quick Introduction using PySpark appeared first on Analytics Vidhya.

Machine Learning 305

Machine Learning Machine Learning Analytics Analytics 305

Analytics Vidhya

MARCH 8, 2023

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

Data Science 345

Data Science Analytics Analytics Apache Hadoop 345

Analytics Vidhya

DECEMBER 12, 2022

Data science is one of India’s rapidly growing and in-demand industries, with far-reaching applications in almost every domain. Not just the leading technology giants in India but medium and small-scale companies are also betting on data science to revolutionize how business operations are performed.

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Analytics Analytics Data Science Data Visualization 342