IBM Journey to AI blog

MARCH 21, 2024

Leveraging distributed storage and processing frameworks such as Apache Hadoop, Spark or Dask accelerates data ingestion, transformation and analysis. Additionally, using in-memory databases and caching mechanisms minimizes latency and improves data access speeds.

Apache Hadoop 90

Apache Hadoop AI AI Natural Language Processing 90

Precisely

MARCH 9, 2023

Hadoop, Snowflake, Databricks and other products have rapidly gained adoption. We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data.

Data Warehouse 58

Data Warehouse Data Lakes Hadoop Apache Hadoop 58

Pickl AI

JULY 29, 2024

Summary: A Hadoop cluster is a collection of interconnected nodes that work together to store and process large datasets using the Hadoop framework. Introduction A Hadoop cluster is a group of interconnected computers, or nodes, that work together to store and process large datasets using the Hadoop framework.

Hadoop 52

Hadoop Clustering Big Data Big Data 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

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

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 21, 2024

Crawlers then store this information in a database for indexing. Structured data can be easily imported into databases or analytical tools. Lead Generation Companies can scrape contact information from websites to build databases of potential customers. This ensures that the indexed information remains current and accurate.

Apache Hadoop 52

Apache Hadoop Hadoop Database Data Quality 52

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 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

Smart Data Collective

MAY 20, 2019

With databases, for example, choices may include NoSQL, HBase and MongoDB but its likely priorities may shift over time. For frameworks and languages, there’s SAS, Python, R, Apache Hadoop and many others. But no matter how difficult it is, data analysts must continue to stay at the forefront of that growth.

Analytics 110

Analytics Analytics Data Analyst Machine Learning 110

Smart Data Collective

SEPTEMBER 15, 2021

Apache Hadoop needs no introduction when it comes to the management of large sophisticated storage spaces, but you probably wouldn’t think of it as the first solution to turn to when you want to run an email marketing campaign. Some groups are turning to Hadoop-based data mining gear as a result.

Hadoop 99

Hadoop Apache Hadoop Predictive Analytics Clustering 99

Analytics Vidhya

MAY 5, 2022

The post A Beginners’ Guide to Apache Hadoop’s HDFS appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. Introduction With a huge increment in data velocity, value, and veracity, the volume of data is growing exponentially with time.

Data Science 241

Data Science Analytics Analytics Apache Hadoop 241

Women in Big Data

OCTOBER 9, 2024

Components of a Big Data Pipeline Data Sources (Collection): Data originates from various sources, such as databases, APIs, and log files. Examples include transactional databases, social media feeds, and IoT sensors. This phase ensures quality and consistency using frameworks like Apache Spark or AWS Glue.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

Mlearning.ai

MAY 16, 2023

It is used to extract data from various sources, transform the data to fit a specific data model or schema, and then load the transformed data into a target system such as a data warehouse or a database. The speed layer is responsible for processing real-time data and storing it in a temporary database.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

JULY 30, 2024

Below are some prominent use cases for Apache NiFi: Data Ingestion from Diverse Sources NiFi excels at collecting data from various sources, including log files, sensors, databases, and APIs. It can connect to various database s, file systems, and cloud storage solutions, enabling seamless data transfer without significant downtime.

ETL 52

ETL Data Lakes Big Data Big Data 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

IBM Journey to AI blog

JANUARY 18, 2023

data platforms and databases), all interacting with one another to provide greater value. A data fabric can consist of multiple data warehouses, data lakes, IoT/Edge devices and transactional databases. Even the transactional databases may also join the fabric network as nodes to offer or consume data assets.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Data Science Dojo

MAY 24, 2024

Java is also widely used in big data technologies, supported by powerful Java-based tools like Apache Hadoop and Spark, which are essential for data processing in AI. Big Data Technologies With the growth of data-driven technologies, AI engineers must be proficient in big data platforms like Hadoop, Spark, and NoSQL databases.

AI 195

AI AI Deep Learning Deep Learning 195