phData

APRIL 26, 2024

One common scenario that we’ve helped many clients with involves migrating data from Hive tables in a Hadoop environment to the Snowflake Data Cloud. Click Create cluster and choose software (Hadoop, Hive, Spark, Sqoop) and configuration (instance types, node count). Configure security (EC2 key pair). Find ElasticMapReduce-master.

Hadoop 52

Hadoop Clustering AWS Database 52

Data Science Connect

JANUARY 27, 2023

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. Understanding how to write efficient and effective SQL queries is essential.

Data Engineering 130

Data Engineering Data Engineering Data Engineer Data Engineering 130

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. Some NoSQL databases are also utilized as platforms for data lakes.

Data Lakes 222

Data Lakes Data Warehouse Hadoop Machine Learning 222

Data Science Dojo

OCTOBER 31, 2024

Database Analyst Description Database Analysts focus on managing, analyzing, and optimizing data to support decision-making processes within an organization. They work closely with database administrators to ensure data integrity, develop reporting tools, and conduct thorough analyses to inform business strategies.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

Analytics Vidhya

JUNE 30, 2022

Introduction Hive is a popular data warehouse built on top of Hadoop that is used by companies like Walmart, Tiktok, and AT&T. This article was published as a part of the Data Science Blogathon. It is an important technology for data engineers to learn and master. It uses a declarative language called HQL, also known […].

Data Warehouse 267

Data Warehouse Hadoop Data Engineering Data Engineering 267

Pickl AI

NOVEMBER 4, 2024

They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes. Data Modelling Data modelling is creating a visual representation of a system or database. Physical Models: These models specify how data will be physically stored in databases.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

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 195

Data Science Machine Learning Machine Learning Data Visualization 195

Smart Data Collective

OCTOBER 14, 2019

With big data careers in high demand, the required skillsets will include: Apache Hadoop. Software businesses are using Hadoop clusters on a more regular basis now. Apache Hadoop develops open-source software and lets developers process large amounts of data across different computers by using simple models. NoSQL and SQL.

Big Data 76

Big Data Big Data Apache Hadoop Hadoop 76

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. 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.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Alation

FEBRUARY 20, 2020

We decided to address these needs for SQL engines over Hadoop in Alation 4.0. It is also used across Alation’s applications, such as our SQL query writing interface, Compose, which produces SmartSuggestions. Further, Alation Compose now benefits from the usage context derived from the query catalogs over Hadoop.

Hadoop 52

Hadoop SQL Database Data Analyst 52

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.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. This is particularly advantageous when dealing with exponentially growing data volumes.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Data Science Dojo

JULY 24, 2023

Its characteristics can be summarized as follows: Volume : Big Data involves datasets that are too large to be processed by traditional database management systems. databases), semi-structured data (e.g., These datasets can range from terabytes to petabytes and beyond. XML, JSON), and unstructured data (e.g., text, images, videos).

Big Data 195

Big Data Big Data Data Engineering Data Engineering 195

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

AUGUST 9, 2024

Variety It encompasses the different types of data, including structured data (like databases), semi-structured data (like XML), and unstructured formats (such as text, images, and videos). It is built on the Hadoop Distributed File System (HDFS) and utilises MapReduce for data processing.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

JUNE 7, 2024

It involves retrieving data from various sources, such as databases, spreadsheets, or even cloud storage. The ETL tool must work with your current systems, support your existing databases and applications, and be able to connect to various data sources. It supports a wide range of databases and provides robust ETL capabilities.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Smart Data Collective

APRIL 8, 2020

Data warehouse, also known as a decision support database, refers to a central repository, which holds information derived from one or more data sources, such as transactional systems and relational databases. They have undergone significant transformation since then, with modern warehouses housing largescale terabyte capacities.

Data Warehouse 135

Data Warehouse Big Data Big Data Business Intelligence 135

Smart Data Collective

NOVEMBER 8, 2020

Unlike the old days where data was readily stored and available from a single database and data scientists only needed to learn a few programming languages, data has grown with technology. Understand the Databases. As a data engineer, you will be primarily working on databases. Just like programming, SQL has multiple dialects.

Data Engineering 83

Data Engineering Data Engineering Data Engineer Data Engineering 83

Pickl AI

APRIL 6, 2023

In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. Sound knowledge of relational databases or NoSQL databases like Cassandra. Hands-on experience working with SQLDW and SQL-DB. Answer : Polybase helps optimize data ingestion into PDW and supports T-SQL.

Azure 52

Azure Data Engineering Data Engineering Data Engineer 52

phData

FEBRUARY 5, 2024

Creating the databases, schemas, roles, and access grants that comprise a data system information architecture can be time-consuming and error-prone. The tool converts the templated configuration into a set of SQL commands that are executed against the target Snowflake environment.

SQL 52

SQL Database Data Quality Data Warehouse 52

Pickl AI

AUGUST 1, 2023

Data Engineers work to build and maintain data pipelines, databases, and data warehouses that can handle the collection, storage, and retrieval of vast amounts of data. Data Storage: Storing the collected data in various storage systems, such as relational databases, NoSQL databases, data lakes, or data warehouses.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

phData

NOVEMBER 8, 2024

Evolution of Open Table Formats Here’s a timeline that outlines the key moments in the evolution of open table formats: 2008 - Apache Hive and Hive Table Format Facebook introduced Apache Hive as one of the first table formats as part of its data warehousing infrastructure, built on top of Hadoop.

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

Mlearning.ai

JULY 10, 2023

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. Tables inherent the key characteristics of its platform BigQuery which provides an upper hand over traditional databases.

SQL 52

SQL Database Apache Hadoop Data Science 52

DagsHub

DECEMBER 11, 2023

DVC lacks crucial relational database features, making it an unsuitable choice for those familiar with relational databases. Dolt Created in 2019, Dolt is an open-source tool for managing SQL databases that uses version control similar to Git. Most developers are familiar with Git for source code versioning.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Database 98

Women in Big Data

SEPTEMBER 7, 2024

Advances in big data technology like Hadoop, Hive, Spark and Machine Learning algorithms have made it possible to interpret and utilize this variety of data effectively. Structured Structured data is quantitative and highly organized, typically managed within relational databases. Examples include HTML files, graphs, and web pages.

Big Data 59

Big Data Big Data Database Machine Learning 59

Pickl AI

NOVEMBER 15, 2023

Unlike traditional databases, Data Lakes enable storage without the need for a predefined schema, making them highly flexible. Unlike traditional databases that require a predefined schema, Data Lakes accommodate both structured and unstructured data. Here it becomes important to highlight the database systems.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 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. They often use tools like SQL and Excel to manipulate data and create reports. Specializing can make you stand out from other candidates.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

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. Data can come from different sources, such as databases or directly from users, with additional sources, including platforms like GitHub, Notion, or S3 buckets.

Machine Learning 52

Machine Learning Machine Learning AI AI 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. The curriculum covers data extraction, querying, and connecting to databases using SQL and NoSQL.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

FEBRUARY 28, 2023

Furthermore, they must be highly efficient in programming languages like Python or R and have data visualization tools and database expertise. Effectively, Data Analysts use other tools like SQL, R or Python, Excel, etc., At length, use Hadoop, Spark, and tools like Pig and Hive to develop big data infrastructures.

Data Analyst 52

Data Analyst Data Scientist Data Science Computer Science 52

IBM Journey to AI blog

AUGUST 29, 2024

Integration: Integrates seamlessly with other data systems and platforms, including Apache Kafka, Spark, Hadoop and various databases. With its easy-to-use and no-code format, users without deep skills in SQL, Java, or Python can leverage events, enriching their data streams with real-time context, irrespective of their role.

Apache Kafka 45

Apache Kafka Hadoop ETL Data Pipeline 45

Pickl AI

NOVEMBER 5, 2024

Tableau supports many data sources, including cloud databases, SQL databases, and Big Data platforms. Tableau’s data connectors include Salesforce, Google Analytics, Hadoop, Amazon Redshift, and others catering to enterprise-level data needs. This makes it an excellent choice for businesses with a diverse tech stack.

Power BI 52

Power BI Tableau Business Intelligence Business Intelligence 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 98

Data Science Analytics Analytics Data Scientist 98

Mlearning.ai

MARCH 15, 2023

Familiarity with Databases; SQL for structured data, and NOSQL for unstructured data. Knowledge of big data platforms like; Hadoop and Apache Spark. 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

DataSeries

AUGUST 15, 2024

Knowledge of Core Data Engineering Concepts Ensure one possess a strong foundation in core data engineering concepts, which include data structures, algorithms, database management systems, data modeling , data warehousing , ETL (Extract, Transform, Load) processes, and distributed computing frameworks (e.g., Hadoop, Spark).

Data Engineering 40

Data Engineering Data Engineering Data Engineer Data Engineering 40

Pickl AI

JULY 8, 2024

Database Extraction: Retrieval from structured databases using query languages like SQL. Common options include: Relational Databases: Structured storage supporting ACID transactions, suitable for structured data. NoSQL Databases: Flexible, scalable solutions for unstructured or semi-structured data.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

Pickl AI

JUNE 19, 2024

Databases and SQL Data doesn’t exist in a vacuum. Understanding relational databases and the Structured Query Language (SQL) is paramount. SQL allows you to retrieve, manipulate, and analyze data stored in relational databases – a fundamental skill for any aspiring Data Scientist.

Data Science 52

Data Science Hypothesis Testing Data Scientist Natural Language Processing 52