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

Sync Computing

NOVEMBER 7, 2024

Despite these limitations, data warehouses, introduced in the late 1980s based on ideas developed even earlier, remain in widespread use today for certain business intelligence and data analysis applications. While data warehouses are still in use, they are limited in use-cases as they only support structured data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 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

Ascend.io

JUNE 8, 2023

Acting as the core infrastructure, data pipelines include the crucial steps of data ingestion, transformation, and sharing. Data Ingestion Data in today’s businesses come from an array of sources, including various clouds, APIs, warehouses, and applications.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

ProjectPro

OCTOBER 28, 2015

Getting data into the Hadoop cluster plays a critical role in any big data deployment. Data ingestion is important in any big data project because the volume of data is generally in petabytes or exabytes. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc.,

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Silectis

JANUARY 3, 2021

Data Catalog An organized inventory of data assets relying on metadata to help with data management. Data Engineering Data engineering is a process by which data engineers make data useful. Data Visualization Graphic representation of a set or sets of data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge. Data orchestration.

Big Data 44

Big Data NoSQL Hadoop Data Lake 44

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake Machine Learning BI 64

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Variety Hadoop stores structured, semi-structured and unstructured data.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Snowflake

JANUARY 18, 2023

The function uses Java streaming methods to handle the rows and specialized column formatting defined by the VCF specification—converting the zipped VCF files into an easy-to-query structured and semi-structured data representation inside Snowflake. All Rights Reserved -- UDTF to ingest gzipped vcf file. import java.util.*;

Pharmaceutical 98

Pharmaceutical AWS Java Healthcare 98

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

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? Databricks – Databricks, the Apache Spark-as-a-service platform, has pioneered the data lakehouse, giving users the options to leverage both structured and unstructured data and offers the low-cost storage features of a data lake.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

SEPTEMBER 6, 2018

The solution combines Cloudera Enterprise , the scalable distributed platform for big data, machine learning, and analytics, with riskCanvas , the financial crime software suite from Booz Allen Hamilton. It supports a variety of storage engines that can handle raw files, structured data (tables), and unstructured data.

Machine Learning 40

Machine Learning Big Data Banking Data Science 40

ProjectPro

NOVEMBER 15, 2021

With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Calcite has chosen to stay out of the data storage and processing business.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 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

Data storage The tools mentioned in the previous section are instrumental in moving data to a centralized location for storage, usually, a cloud data warehouse, although data lakes are also a popular option. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

Monte Carlo

JULY 10, 2023

Data sampling If you’re working with large data sets where it’s impractical to evaluate every attribute or record, you can systematically sample your data set to estimate completeness. Be sure to use random sampling to select representative subsets of your data.

Data Collection 40

Data Collection Data Governance Government Data 40

phData: Data Engineering

JULY 18, 2023

Demands on the cloud data warehouse are also evolving to require it to become more of an all-in-one platform for an organization’s analytics needs. Enter Snowflake The Snowflake Data Cloud is one of the most popular and powerful CDW providers. Allowing data diff analysis and code generation.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

OCTOBER 20, 2021

Experiment to see what works best for your data, automate it using pipelines, and then monitor the performance of the workflow. Data: Data Engineering Pipelines Data is everything. Make sure that the quality of data works for your use case. 29) What is the difference between MLOps and DevOps?

Machine Learning 52

Machine Learning Algorithm Data Science Government 52