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

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

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 Unstructured Data Government 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 Data Warehouse ETL Tools 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 Data Science Certification Big Data 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 Business Intelligence Data Cleanse 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 Machine Learning BI 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 Unstructured Data Data Warehouse 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 Raw Data SQL 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

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 AWS 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

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