Striim

SEPTEMBER 11, 2024

In an ETL-based architecture, data is first extracted from source systems, then transformed into a structured format, and finally loaded into data stores, typically data warehouses. This method is advantageous when dealing with structured data that requires pre-processing before storage.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Edureka

JUNE 1, 2023

This is where AWS Data Analytics comes into action, providing businesses with a robust, cloud-based data platform to manage, integrate, and analyze their data. In this blog, we’ll explore the world of Cloud Data Analytics and a real-life application of AWS Data Analytics.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

Towards Data Science

JANUARY 16, 2024

New data formats emerged — JSON, Avro, Parquet, XML etc. Data lakes were introduced to store the new data formats. Image by the author 2010 to 2020 - The Cloud Data Warehouse Enterprises now wanted quick data analytics without yesterday’s constraints of flexibility, processing power and scale.

Data Warehouse 95

Data Warehouse Data Architecture Relational Database NoSQL 95

U-Next

MARCH 1, 2023

What is a data lake, and how does it differ from a data warehouse? Data lakes contain raw, unstructured data of an organization, which can be stored indefinitely – either immediately or in the future. What are the components of AWS Kinesis?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Data Engineering Weekly

MAY 5, 2024

link] LinkedIn: LakeChime - A Data Trigger Service for Modern Data Lakes LinkedIn points out two critical flaws in a partitioned approach to data management. The granularity of partition creation constrained data consumption. However, the Map and Array comes with its cost.

Data Engineering 67

Data Engineering Data Engineer Engineering Google Cloud 67

Rockset

JULY 29, 2022

This fast, serverless, highly scalable, and cost-effective multi-cloud data warehouse has built-in machine learning, business intelligence, and geospatial analysis capabilities for querying massive amounts of structured and semi-structured data. This is true for the three data warehouses mentioned above.

Data Analytics 52

Data Analytics Data Warehouse Datasets Cloud 52

AltexSoft

AUGUST 4, 2021

Since data marts provide analytical capabilities for a restricted area of a data warehouse, they offer isolated security and isolated performance. Data mart vs data warehouse vs data lake vs OLAP cube. Data lakes, data warehouses, and data marts are all data repositories of different sizes.

Data Lake 64

Data Lake Data Warehouse ETL Tools Database 64

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. This feature allows for a more flexible exploration of data.

Data Management 52

Data Management Management Data Lake Data Governance 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

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

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

Data Lake 52

Data Lake Data Warehouse ETL Tools Data Pipeline 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Cloudera

NOVEMBER 15, 2024

However, there is a fundamental challenge standing in the way of being successful: data. By breaking down data silos and integrating log data from multiple sources, Cloudera empowers defenders with the real-time analytics to respond to threats swiftly.

Metadata 59

Metadata Unstructured Data Data Lake Government 59

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Edureka

JULY 4, 2024

Azure Synapse is Microsoft’s cloud-based analytics powerhouse. It’s a Swiss Army knife for data pros, merging data integration, warehousing, and big data analytics into one sleek package. No need to move the data around first. What is Azure Synapse?

Data Lake 40

Data Lake Pipeline-centric Data Warehouse ETL Tools 40

AltexSoft

MARCH 14, 2023

Built around a cloud data warehouse, data lake, or data lakehouse. Modern data stack tools are designed to integrate seamlessly with cloud data warehouses such as Redshift, Bigquery, and Snowflake, as well as data lakes or even the child of the first two — a data lakehouse.

IT 59

IT Data Warehouse Data Governance Data Lake 59

AltexSoft

AUGUST 22, 2022

A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., to provide a unified view of all enterprise data.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

ProjectPro

JANUARY 24, 2023

You can leverage AWS Glue to discover, transform, and prepare your data for analytics. In addition to databases running on AWS, Glue can automatically find structured and semi-structured data kept in your data lake on Amazon S3, data warehouse on Amazon Redshift, and other storage locations.

AWS 52

AWS ETL Tools Data Lake Scala 52

Edureka

FEBRUARY 7, 2023

Dynamic data masking serves several important functions in data security. One can use polybase: From Azure SQL Database or Azure Synapse Analytics, query data kept in Hadoop, Azure Blob Storage, or Azure Data Lake Store. It does away with the requirement to import data from an outside source.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Rockset

APRIL 26, 2023

Offline feature store : Detecting anomalies requires historical data in order to have a baseline for comparisons. This data tends to be slow changing and is stored in an offline feature store. This could be a cloud data warehouse, a data lake, or a database. The database has two primary jobs.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Striim

AUGUST 22, 2024

Collect data in real time Every organization can leverage valuable real-time data. Real-time analytics is made possible by the way the data is processed. Batch Processing In data analytics, batch processing involves first storing large amounts of data for a period and then analyzing it as needed.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

Monte Carlo

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses. Let the data drive the data pipeline architecture.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Monte Carlo

AUGUST 31, 2023

Data pipelines can handle both batch and streaming data, and at a high-level, the methods for measuring data quality for either type of asset are much the same. What is Data Quality? Data quality as a concept is not novel – “ data quality ” has been around as long as humans have been collecting data!

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

APRIL 25, 2023

Key features: Robust data visualization capabilities Seamless integration with Microsoft tools Easy-to-use interface 2. Looker Looker is a business intelligence (BI) and data analytics platform that provides a unified view of data from different sources.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

ProjectPro

FEBRUARY 16, 2023

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades. Q) What ETL does Amazon use? A) Amazon uses AWS Glue as its ETL tool.

AWS 52

AWS Data Management ETL Tools Management 52

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.

Big Data 44

Big Data NoSQL Hadoop Data Lake 44

Silectis

JANUARY 3, 2021

Data Ingestion The process by which data is moved from one or more sources into a storage destination where it can be put into a data pipeline and transformed for later analysis or modeling. Data Integration Combining data from various, disparate sources into one unified view.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JULY 27, 2021

Also, you will find some interesting data engineer interview questions that have been asked in different companies (like Facebook, Amazon, Walmart, etc.) that leverage big data analytics and tools. Preparing for data engineer interviews makes even the bravest of us anxious. Structured data usually consists of only text.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Monte Carlo

JANUARY 25, 2023

When it comes to the question of building or buying your data stack, there’s never a one-size-fits-all solution for every data team—or every component of your data stack. The three most popular solutions for data storage and compute include the data warehouse, data lake, and data lakehouse.

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

Knowledge Hut

DECEMBER 26, 2023

Python for Data Analysis By Wes McKinney Online Along with Machine Learning, you also need to learn about Python, a widely used programming language in the field of Data Analytics. Bruce, and Peter Gedeck) Naked Statistics: Stripping the Dread from the Data (Author: Charles Wheelan) 3.

Data Science 52

Data Science Programming Language Scala R (Programming) 52

ProjectPro

JANUARY 31, 2022

As a result, having a central repository to safely store all data and further examine it to make informed decisions becomes necessary for enterprises. This is the reason why we need Data Warehouses. What is Snowflake Data Warehouse? To increase reliability over Data Lake 1.0, What Does Snowflake Do?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Rockset

JULY 6, 2022

This radical design choice made NoSQL databases — document databases, key-value stores, column-oriented databases and graph databases — great at storing huge amounts of data of varying kinds together, whether it is structured, semi-structured or polymorphic. Take the Hive analytics database that is part of the Hadoop stack.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52