Knowledge Hut

MARCH 28, 2024

They handle large amounts of structured and unstructured data and use Azure services to develop data processing and analytics pipelines. Role Level: Intermediate Responsibilities Design and develop big data solutions using Azure services like Azure HDInsight, Azure Databricks, and Azure Data Lake Storage.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? Amazon Redshift – Amazon Redshift, one of the most widely used options, sits on top of Amazon Web Services (AWS) and easily integrates with other data tools in the space.

Building 52

Building BI Data Lake Data Governance 52

ProjectPro

FEBRUARY 8, 2023

Create The Connector for Source Database The first step is having the source database, which can be any S3, Aurora, and RDS that can hold structured and unstructured data. Glue works absolutely fine with structured as well as unstructured data.

AWS 98

AWS Scala Metadata Data Lake 98

Monte Carlo

APRIL 24, 2023

We continuously hear data professionals describe the advantage of the Snowflake platform as “it just works.” Snowpipe and other features makes Snowflake’s inclusion in this top data lake vendors list a no-brainer. Not to mention seamless integration with the Oracle ecosystem.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Knowledge Hut

JUNE 26, 2023

Using big data, we are able to transform unstructured data, such as customer reviews, into actionable insights, which enables businesses to better understand how and why customers prefer their products or services and to make improvements to their operations as quickly as is practically possible.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

AltexSoft

MAY 14, 2021

Big Data analytics encompasses the processes of collecting, processing, filtering/cleansing, and analyzing extensive datasets so that organizations can use them to develop, grow, and produce better products. Big Data analytics processes and tools. Data ingestion. Let’s take a closer look at these procedures.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

AUGUST 24, 2021

They are also often expected to prepare their dataset by web scraping with the help of various APIs. 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.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

phData: Data Engineering

JANUARY 3, 2022

Analyzing the data, ensuring it adheres to data governance rules and regulations. Understanding the pros and cons of data storage and query options. For example, an enterprise might be using Amazon Web Services (AWS) as a cloud provider, and you want to store and query data from various systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

ProjectPro

MAY 31, 2021

The project develops a data processing chain in a big data environment using Amazon Web Services (AWS) cloud tools, including steps like dimensionality reduction and data preprocessing and implements a fruit image classification engine. are examples of semi-structured data. How Big Data Works?

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

OCTOBER 20, 2021

This would include the automation of a standard machine learning workflow which would include the steps of Gathering the data Preparing the Data Training Evaluation Testing Deployment and Prediction This includes the automation of tasks such as Hyperparameter Optimization, Model Selection, and Feature Selection.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52