AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., They enable the connection of various data sources to the Hadoop environment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Silectis

JANUARY 3, 2021

Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Data Engineering Weekly

MARCH 24, 2023

Drawback #1: Not Every Database Supports Transaction The relational database support transaction for multiple mutation statements. However, if you use systems like DynamoDB, the transaction support falls under the application or the Data Access Layer. However, Event sourcing comes with a few major limitations.

Engineering 67

Engineering Data Transportation Database 67

AltexSoft

SEPTEMBER 23, 2021

An ETL approach in the DW is considered slow, as it ships data in portions (batches.) The structure of data is usually predefined before it is loaded into a warehouse, since the DW is a relational database that uses a single data model for everything it stores.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

ProjectPro

NOVEMBER 15, 2021

DataFrames are used by Spark SQL to accommodate structured and semi-structured data. You can also access data through non-relational databases such as Apache Cassandra, Apache HBase, Apache Hive, and others like the Hadoop Distributed File System. However, Trino is not limited to HDFS access.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

OCTOBER 15, 2014

Hive- Performance Benchmarking Hive vs Pig Pig vs Hive - Differences Pig Hive Procedural Data Flow Language Declarative SQLish Language For Programming For creating reports Mainly used by Researchers and Programmers Mainly used by Data Analysts Operates on the client side of a cluster. Does not have a dedicated metadata database.

Hadoop 52

Hadoop Java Unstructured Data SQL 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Note, though, that not any type of web scraping is legal.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Snowflake

JANUARY 18, 2023

But legacy systems and data silos prevent easy and secure data sharing. Snowflake can help life sciences companies query and analyze data easily, efficiently, and securely. Snowflake’s ability to scale compute resources easily and dynamically without limits, but only when needed, combines performance with cost-effectiveness.

Pharmaceutical 98

Pharmaceutical AWS Java Healthcare 98

Knowledge Hut

DECEMBER 21, 2023

NoSQL This database management system has been designed in a way that it can store and handle huge amounts of semi-structured or unstructured data. Avro creates binary data which can be both compressed as well as split. Avro creates a file that stores all the data and saves the schema in the metadata section.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Rockset

AUGUST 2, 2023

This enrichment data has changing schemas and new data providers are constantly being added to enhance the insights, making it challenging for Windward to support using relational databases with strict schemas. They used MongoDB as their metadata store to capture vessel and company data.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

AltexSoft

JULY 29, 2022

How HDFS master-slave structure works. A master node called NameNode maintains metadata with critical information, controls user access to the data blocks, makes decisions on replications, and manages slaves. You can change this parameter manually but the system won’t be able to effectively deal with myriads of tiny data pieces.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 52

ProjectPro

AUGUST 24, 2016

Table of Contents Need for HBase HBase –Understanding the Basics HBase Architecture Explained Components of Apache HBase Architecture HMaster Region Server Zookeeper Need for HBase Apache Hadoop has gained popularity in the big data space for storing, managing and processing big data as it can handle high volume of multi-structured data.

Architecture 40

Architecture IT Hadoop NoSQL 40

ProjectPro

JUNE 23, 2016

Sqoop is compatible with all JDBC compatible databases. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Apache Sqoop uses Hadoop MapReduce to get data from relational databases and stores it on HDFS. It has a connector based architecture.

Hadoop 40

Hadoop MySQL Relational Database Java 40

AltexSoft

OCTOBER 8, 2021

The prevailing part of users claim that it is quite easy to configure and manage data flows with Oracle’s graphical tools. Data profiling and cleansing. The tool supports all sorts of data loading and processing: real-time, batch, streaming (using Spark), etc. This works for both batch and real-time jobs. Pre-built connectors.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

U-Next

SEPTEMBER 29, 2022

There is no guarantee that a company has a data-driven culture or is data-driven merely because it collects a great deal of data. In order to make informed decisions, organizations need to leverage data. . Types of Data in an Organization . A structured data record consists of a very fixed field of data.

Management 52

Management Unstructured Data Data Government 52

ProjectPro

NOVEMBER 22, 2021

StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. PySpark imports the StructType class from pyspark.sql.types to describe the DataFrame's structure. We can store the data and metadata in a checkpointing directory. appName('ProjectPro').getOrCreate()

Hadoop 52

Hadoop Python Datasets Metadata 52

AltexSoft

MARCH 14, 2023

Databases store key information that powers a company’s product, such as user data and product data. The ones that keep only relational data in a tabular format are called SQL or relational database management systems (RDBMSs). Data storage component in a modern data stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59