ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. CDP Data Lake cluster versions – CM 7.4.0,

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

Towards Data Science

JULY 21, 2023

In this article, we’ll present you with the Five Layer Data Stack — a model for platform development consisting of five critical tools that will not only allow you to maximize impact but empower you to grow with the needs of your organization. However, this won’t simply be where you store your data — it’s also the power to activate it.

Building 98

Building Business Intelligence BI Cloud Storage 98

AltexSoft

FEBRUARY 11, 2023

To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. Sample of a high-level data architecture blueprint for Azure BI programs.

Data Architect 87

Data Architect Certification Generalist Big Data 87

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. The data lakes store data from a wide variety of sources, including IoT devices, real-time social media streams, user data, and web application transactions.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 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

Cloudera

JUNE 22, 2023

Financial services firms can leverage the near-infinite capacity of the cloud while leveraging on-premises resources to meet demanding performance and compliance requirements. It integrates data from databases, cloud or RESTful APIs, and real-time, streaming feeds, as well as unstructured data from document databases and other sources.

Data Cleanse 66

Data Cleanse Data Governance Unstructured Data Cloud Storage 66

Monte Carlo

AUGUST 25, 2023

At the same time, 81% of IT leaders say their C-suite has mandated no additional spending or a reduction of cloud costs. Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. But, the options for data storage are evolving quickly. Or maybe both.)

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Knowledge Hut

JUNE 26, 2023

A complete end-to-end stream processing pipeline is shown here using an architectural diagram. The pipeline in this reference design collects data from two different sources, then conducts a join operation on related records from each stream, then enriches the output, and finally produces an average.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Precisely

OCTOBER 10, 2024

With data democratization, the availability of data and associated analysis tools extends far beyond the limited group of experts who have a data science background. Organizations are evaluating modern data management architectures that will support wider data democratization. Read Data democracy: Why now?

Data Governance 52

Data Governance Government Data Unstructured Data 52

ProjectPro

JANUARY 24, 2023

Tired of relentlessly searching for the most effective and powerful data warehousing solutions on the internet? This blog is your comprehensive guide to Google BigQuery, its architecture, and a beginner-friendly tutorial on how to use Google BigQuery for your data warehousing activities. Search no more! Did you know ?

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52

Tweag

APRIL 19, 2023

Thankfully, cloud-based infrastructure is now an established solution which can help do this in a cost-effective way. As a simple solution, files can be stored on cloud storage services, such as Azure Blob Storage or AWS S3, which can scale more easily than on-premises infrastructure. But as it turns out, we can’t use it.

Medical 62

Medical Process Cloud Bytes 62

Monte Carlo

JANUARY 27, 2024

Those tools include: Table of Contents Cloud storage and compute Data transformation Business Intelligence (BI) Data observability Data orchestration The most important part? Cloud storage and compute Whether you’re stacking data tools or pancakes, you always build from the bottom up.

Building 52

Building Business Intelligence Cloud Storage BI 52

AltexSoft

MARCH 30, 2023

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. The relatively new storage architecture powering Databricks is called a data lakehouse. Databricks lakehouse platform architecture.

Scala 64

Scala Data Lake Machine Learning BI 64

Meltano

OCTOBER 5, 2022

Automation Automation is an essential factor in data management, as it helps save both time and money while increasing efficiency and reducing errors. Meltano enables the automation of data delivery from various sources at the same time. Testing Data Quality Untested and undocumented data can result in unstable data and pipeline debt.

Data Engineering 52

Data Engineering Data Engineer Engineering Raw Data 52

Knowledge Hut

SEPTEMBER 26, 2023

Organizations can harness the power of the cloud, easily scaling resources up or down to meet their evolving data processing demands. Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

Knowledge Hut

JULY 24, 2023

NoSQL cloud databases offer non-relational, schema-less, and horizontally scalable databases. Examples include Amazon DynamoDB and Google Cloud Datastore. Cloud databases that are object-oriented, like Amazon S3 and Google Cloud Storage.

Database 52

Database NoSQL Management Relational Database 52

ProjectPro

JANUARY 19, 2022

An Azure Data Engineer is a highly qualified expert responsible for integrating, transforming, and merging data from various structured and unstructured sources into a structure used to construct analytics solutions. Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

Edureka

FEBRUARY 9, 2023

An Azure Data Engineer is a highly qualified expert who is in charge of integrating, transforming, and merging data from various structured and unstructured sources into a structure that can be used to build analytics solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Striim

AUGUST 22, 2024

“Sometimes there’s so much data that old batch processing (late at night once a day or once a week) just doesn’t have time to move all data and hence the only way to do it is trickle feed data via CDC,” says Dmitriy Rudakov, Director of Solution Architecture at Striim.

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

ProjectPro

AUGUST 11, 2021

Table of Contents Data Lake vs Data Warehouse - The Differences Data Lake vs Data Warehouse - The Introduction What is a Data warehouse? Data Warehouse Architecture What is a Data lake? Data is generally not loaded into a data warehouse unless a use case has been defined for the data.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Central to this transformation are two shifts.

Data Lake 52

Data Lake Data Warehouse ETL Tools Data Pipeline 52

ProjectPro

JULY 30, 2021

What is Cloud Computing? Cloud Computing is the grouping of networks, hardware, services, and storage that delivers/sells computing over the internet. Building data storage and computing architecture locally were getting more expensive during the advent of Big Data technologies. What is cloud-native?

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

Monte Carlo

AUGUST 19, 2023

Data-first companies have embraced data platforms as an effective way to aggregate, operationalize, and democratize data at scale across the organization. Regardless of which side you take, you quite literally cannot build a modern data platform without investing in cloud storage and compute.

Building 52

Building BI Data Lake Data Governance 52

Knowledge Hut

DECEMBER 27, 2023

Many business owners and professionals are interested in harnessing the power locked in Big Data using Hadoop often pursue Big Data and Hadoop Training. What is Big Data? Big data is often denoted as three V’s: Volume, Variety and Velocity. Pros: Handles huge data volume very fast without any single point of failure.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

MAY 31, 2021

Data Description: You will use the Covid-19 dataset(COVID-19 Cases.csv) from data.world , for this project, which contains a few of the following attributes: people_positive_cases_count county_name case_type data_source Language Used: Python 3.7 Big Data Analytics Projects for Students on Chicago Crime Data Analysis with Source Code 11.

Big Data 52

Big Data Coding Project Hadoop 52

Data Engineering Weekly

DECEMBER 18, 2024

These trends mark a decisive move towards hybrid and energy-efficient computing architectures, bridging the gap between performance, cost, and privacy in AI applications. Inspired by the human brain, Neuromorphic chips promise unparalleled energy efficiency and the ability to process unstructured data locally on devices.

Data Engineering 113

Data Engineering Data Engineer Engineering Data Lake 113

Edureka

APRIL 15, 2025

Following that, we will examine the Microsoft Fabric Data Engineer Associate Microsoft Fabric Data Engineer Associate About the Certification This professional credential verifies your proficiency in implementing data engineering solutions using Microsoft’s unified analytics platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

ProjectPro

NOVEMBER 30, 2021

In extract-transform-load (ETL), data is obtained from multiple sources, transformed, and stored in a single data warehouse, with access to data analysts , data scientists , and business analysts for data visualization and statistical analysis model building, forecasting, etc.

Process 52

Process Data Warehouse Data Pipeline AWS 52