ProjectPro

JUNE 6, 2025

Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it. The query processing layer is separated from the disk storage layer in the Snowflake data architecture.

Architecture 56

Architecture IT Data Warehouse Amazon Web Services 56

Edureka

APRIL 14, 2025

Microsoft offers a leading solution for business intelligence (BI) and data visualization through this platform. It empowers users to build dynamic dashboards and reports, transforming raw data into actionable insights. However, it leans more toward transforming and presenting cleaned data rather than processing raw datasets.

BI 40

BI Business Intelligence Raw Data Retail 40

ProjectPro

JUNE 6, 2025

Key Responsibilities of a Data Engineer Here are the skills to hone for fulfilling the day-to-day responsibilities of a data engineer: Obtain data from third-party providers with the help of robust API integrations. Build, Design, and maintain data architectures using a systematic approach that satisfies business needs.

Data Engineering 49

Data Engineering Data Engineer Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

Here are some examples of the responsibilities handled by Data Engineers: Ingest data from different data sources (Based on the Business Use Case) Scheduling Data Received based on a pre-defined Data Collection Methodology. Maintain the data architecture over time and its scalability.

Data Science 40

Data Science Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 40

Big Data Hadoop Relational Database NoSQL 40

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 Data Lake MongoDB 59

Knowledge Hut

DECEMBER 26, 2023

Businesses benefit at large with these data collection and analysis as they allow organizations to make predictions and give insights about products so that they can make informed decisions, backed by inferences from existing data, which, in turn, helps in huge profit returns to such businesses. What is the role of a Data Engineer?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems. What Is ELT? So, what exactly is ELT?

Raw Data 52

Raw Data Data Warehouse Data Cleanse Transportation 52

Knowledge Hut

JANUARY 18, 2024

4 Purpose Utilize the derived findings and insights to make informed decisions The purpose of AI is to provide software capable enough to reason on the input provided and explain the output 5 Types of Data Different types of data can be used as input for the Data Science lifecycle.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

AltexSoft

AUGUST 29, 2023

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. This article explains what a data lake is, its architecture, and diverse use cases. Structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

JUNE 6, 2025

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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 Data Lake 52

Monte Carlo

APRIL 1, 2021

Unstructured data is problematic as it relates to data catalogs because it’s not organized, and if it is, it’s often not declared as organized. While modern data architectures, including data lakes, are often distributed, data catalogs are usually not, treating data like a one-dimensional entity.

Data Lake 52

Data Lake Data Warehouse Government Metadata 52

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake. Lakehouse architecture.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 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. Their task is straightforward: take the raw data and transform it into a structured, coherent format.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Knowledge Hut

NOVEMBER 28, 2023

Here Data Science becomes relevant as it deals with converting unstructured and messy data into structured data sets for actionable business insights. Data Science is also concerned with analyzing, exploring, and visualizing data, thereby assisting the company's growth.

Data Architect 52

Data Architect Certification Data Science Data Warehouse 52

Knowledge Hut

OCTOBER 30, 2023

The role of a Power BI developer is extremely imperative as a data professional who uses raw data and transforms it into invaluable business insights and reports using Microsoft’s Power BI. Ensure compliance with data protection regulations. Develop a long-term vision for Power BI implementation and data analytics.

BI 52

BI Data Cleanse Business Intelligence Business Analyst 52

Rockset

AUGUST 2, 2023

All of these assessments go back to the AI insights initiative that led Windward to re-examine its data stack. The steps Windward takes to create proprietary data and AI insights As Windward operated in a batch-based data stack, they stored raw data in S3.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

ProjectPro

FEBRUARY 16, 2023

Your SQL skills as a data engineer are crucial for data modeling and analytics tasks. Making data accessible for querying is a common task for data engineers. Collecting the raw data, cleaning it, modeling it, and letting their end users access the clean data are all part of this process.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

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 BI Google Cloud 64

Monte Carlo

AUGUST 31, 2023

We’ll take a closer look at variables that can impact your data next. Migration to the cloud Twenty years ago, your data warehouse (a place to transform and store structured data) probably would have lived in an office basement, not on AWS or Azure. What is a decentralized data architecture?

Data Lake 52

Data Lake Data Pipeline Data Warehouse Unstructured Data 52

Rockset

JANUARY 28, 2020

Testing new functionality on their transactional data store is costly and can impact production. Ad hoc queries to measure the accuracy of the checkout process in real time are not possible with traditional data architectures. When in the experimental phase, quick schema changes are required when analyzing their data.

Retail 40

Retail Google Cloud Data Lake Raw Data 40

Monte Carlo

JUNE 14, 2023

Data transformation dbt – Short for data build tool, is the open source leader for transforming data once it’s loaded into your warehouse. Dataform – Now part of the Google Cloud , Dataform allows you to transform raw data from your warehouse into something usable by BI and analytics tools.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 52

Big Data Hadoop Relational Database NoSQL 52

ProjectPro

JANUARY 31, 2022

Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it. The query processing layer is separated from the disk storage layer in the Snowflake data architecture.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

NOVEMBER 14, 2015

This data can be analysed using big data analytics to maximise revenue and profits. Big data technologies used: Microsoft Azure, Azure Data Factory, Azure Databricks, Spark Big Data Architecture: This sample Hadoop real-time project starts off by creating a resource group in azure.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

This data can be analysed using big data analytics to maximise revenue and profits. Big data technologies used: Microsoft Azure, Azure Data Factory, Azure Databricks , Spark Big Data Architecture: This sample Hadoop real-time project starts off by creating a resource group in azure.

Hadoop 40

Hadoop Project Media Big Data 40

ProjectPro

JUNE 6, 2025

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need. Data Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

JULY 22, 2016

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need. Data Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

MAY 31, 2021

To build a big data project, you should always adhere to a clearly defined workflow. Before starting any big data project, it is essential to become familiar with the fundamental processes and steps involved, from gathering raw data to creating a machine learning model to its effective implementation.

Big Data 52

Big Data Coding Project Hadoop 52

Edureka

MAY 28, 2025

Business researchers, data engineers, and decision makers can use BI tools, SQL clients, and other less advanced (i.e., not data science) analytics apps to access data in data warehouses. What Is a Data Lake? The relational data in data warehouses has already been “cleaned.”

Data Lake 40

Data Lake Data Warehouse Unstructured Data Business Intelligence 40