Mlearning.ai

MAY 23, 2023

Familiarity with libraries like pandas, NumPy, and SQL for data handling is important. This includes skills in data cleaning, preprocessing, transformation, and exploratory data analysis (EDA). Additionally, knowledge of model evaluation, hyperparameter tuning, and model selection is valuable.

Data Science 52

Data Science Data Scientist Apache Hadoop Machine Learning 52

Pickl AI

JULY 18, 2023

SQL: Mastering Data Manipulation Structured Query Language (SQL) is a language designed specifically for managing and manipulating databases. 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.

Data Science 52

Data Science SQL Data Scientist Apache Hadoop 52

Pickl AI

MAY 29, 2024

Programming Languages (Python, R, SQL) Proficiency in programming languages is crucial. SQL is indispensable for database management and querying. Knowledge of supervised and unsupervised learning and techniques like clustering, classification, and regression is essential.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Dataconomy

JULY 24, 2023

” 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. Familiarity with regression techniques, decision trees, clustering, neural networks, and other data-driven problem-solving methods is vital.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

Smart Data Collective

APRIL 8, 2020

This data is then processed, transformed, and consumed to make it easier for users to access it through SQL clients, spreadsheets and Business Intelligence tools. The company works consistently to enhance its business intelligence solutions through innovative new technologies including Hadoop-based services.

Data Warehouse 134

Data Warehouse Big Data Big Data Business Intelligence 134

Data Science Dojo

JANUARY 12, 2023

Hadoop systems and data lakes are frequently mentioned together. Data is loaded into the Hadoop Distributed File System (HDFS) and stored on the many computer nodes of a Hadoop cluster in deployments based on the distributed processing architecture.

Data Lakes 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

Pickl AI

MAY 31, 2023

After that, move towards unsupervised learning methods like clustering and dimensionality reduction. You should be skilled in using a variety of tools including SQL and Python libraries like Pandas. It includes regression, classification, clustering, decision trees, and more.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Data Science Dojo

JULY 24, 2023

Clusters : Clusters are groups of interconnected nodes that work together to process and store data. Clustering allows for improved performance and fault tolerance as tasks can be distributed across nodes. Each node is capable of processing and storing data independently.

Big Data 195

Big Data Big Data Data Engineering Data Engineer 195

Smart Data Collective

SEPTEMBER 8, 2021

Extract : In this step, data is extracted from a vast array of sources present in different formats such as Flat Files, Hadoop Files, XML, JSON, etc. Here are few best Open-Source ETL tools on the market: Hadoop : Hadoop distinguishes itself as a general-purpose Distributed Computing platform.

ETL 93

ETL Hadoop Data Warehouse Data Pipeline 93

phData

FEBRUARY 5, 2024

Setting up the Information Architecture Setting up an information architecture during migration to Snowflake poses challenges due to the need to align existing data structures, types, and sources with Snowflake’s multi-cluster, multi-tier architecture. Essentially, it functions like Google Translate — but for SQL dialects.

SQL 52

SQL Database Data Quality Data Warehouse 52

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. Follow Industry Trends.

Data Engineering 81

Data Engineering Data Engineer Data Engineering Data Engineering 81

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. As a declarative language, SQL is very powerful in allowing users from all backgrounds to ask questions about data. What is Snowflake’s Snowpark? Why Does Snowpark Matter?

SQL 98

SQL Python Data Lakes Machine Learning 98

IBM Journey to AI blog

SEPTEMBER 25, 2023

This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success. This allowed them to focus on SQL-based query optimization to the nth degree. They also put process automation in place to quickly set up and take down clusters.

Data Lakes 87

Data Lakes Analytics Analytics Clustering 87

IBM Journey to AI blog

JULY 5, 2023

In the case of Hadoop, one of the more popular data lakes, the promise of implementing such a repository using open-source software and having it all run on commodity hardware meant you could store a lot of data on these systems at a very low cost. It gained rapid popularity given its support for data transformations, streaming and SQL.

Data Lakes 61

Data Lakes Data Warehouse Data Governance SQL 61