BOOKS - Architecting a Modern Data Warehouse for Large Enterprises
Architecting a Modern Data Warehouse for Large Enterprises - Anjani Kumar, Abhishek Mishra, Sanjeev Kumar 2024 PDF Apress BOOKS
ECO~15 kg CO²

1 TON

Views
11282

Telegram
 
Architecting a Modern Data Warehouse for Large Enterprises
Author: Anjani Kumar, Abhishek Mishra, Sanjeev Kumar
Year: 2024
Pages: 378
Format: PDF
File size: 10.1 MB
Language: ENG



Pay with Telegram STARS
The book "Architecting a Modern Data Warehouse for Large Enterprises" by David L. Simpson, published in 2019, provides a comprehensive guide to designing, building, and maintaining a modern data warehouse for large enterprises. The author emphasizes the importance of understanding the evolution of technology and its impact on society, as well as the need to develop a personal paradigm for perceiving the technological process of developing modern knowledge as the basis for the survival of humanity and the unification of people in a warring state. The book begins by discussing the challenges faced by large enterprises when it comes to managing their data assets. With the increasing amount of data being generated every day, it has become essential for organizations to have a robust data management system in place to make sense of this information and use it to inform their business decisions. However, traditional data warehousing solutions are often insufficient for handling the scale and complexity of big data, leading to the need for a more modern approach. The author then delves into the concept of a modern data warehouse, which is designed to handle the vast amounts of structured and unstructured data that enterprises generate.
''

You may also be interested in:

Architecting a Modern Data Warehouse for Large Enterprises: Build Multi-cloud Modern Distributed Data Warehouses with Azure and AWS
Architecting a Modern Data Warehouse for Large Enterprises
Architecting a Modern Data Warehouse for Large Enterprises
Deciphering Data Architectures Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh
Deciphering Data Architectures Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh
Data Warehouse and Data Mining Concepts, techniques and real life applications
Data Warehouse and Data Mining Concepts, techniques and real life applications
Data Warehouse and Data Mining: Concepts, techniques and real life applications (English Edition)
Building a Scalable Data Warehouse with Data Vault 2.0
Foundations for Architecting Data Solutions Managing Successful Data Projects
Quick Start Guide to Azure Data Factory, Azure Data Lake Server, and Azure Data Warehouse
Data Modeling with Microsoft Power BI Self-Service and Enterprise Data Warehouse with Power BI (Final Release)
Data Modeling with Microsoft Power BI Self-Service and Enterprise Data Warehouse with Power BI (Final Release)
Data Warehouse Requirements Engineering
Programming Hive Data Warehouse and Query Language for Hadoop
Unlocking dbt Design and Deploy Transformations in Your Cloud Data Warehouse
Managing Cloud Native Data on Kubernetes Architecting Cloud Native Data Services Using Open Source Technology (Final)
Managing Cloud Native Data on Kubernetes: Architecting Cloud Native Data Services Using Open Source Technology
Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema
Architecting IoT Solutions on Azure Conquering Complexity for Scalable Device and Data Management
Architecting Data and Machine Learning Platforms: Enable Analytics and AI-Driven Innovation in the Cloud
Architecting IoT Solutions on Azure Conquering Complexity for Scalable Device and Data Management
Modern Data Architectures with Python: A practical guide to building and deploying data pipelines, data warehouses, and data lakes with Python
Architecting Data and Machine Learning Platforms Enable Analytics and AI-Driven Innovation in the Cloud (Final)
Architecting Data and Machine Learning Platforms Enable Analytics and AI-Driven Innovation in the Cloud (Final)
Snowflake The Definitive Guide Architecting, Designing, and Deploying on the Snowflake Data Cloud
Mastering Azure Analytics Architecting in the Cloud with Azure Data Lake, HDInsight, and Spark
Big Data Governance Modern Data Management Principles for Hadoop, NoSQL & Big Data Analytics
Data Mining and Exploration From Traditional Statistics to Modern Data Science
Delta Lake The Definitive Guide Modern Data Lakehouse Architectures with Data Lakes (Final Release)
Delta Lake The Definitive Guide Modern Data Lakehouse Architectures with Data Lakes (Final Release)
Data Labeling in Machine Learning with Python: Explore modern ways to prepare labeled data for training and fine-tuning ML and generative AI models
Data Fabric as Modern Data Architecture
The Modern Business Data Analyst: A Case Study Introduction into Business Data Analytics with CRISP-DM and R
Data Modeling with SAP BW 4HANA 2.0: Implementing Agile Data Models Using Modern Modeling Concepts
Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data (Princeton Series in Modern Observational Astronomy, 1)
Modern Data Architecture on Azure Design Data-centric Solutions on Microsoft Azure
Modern Data Architecture on Azure Design Data-centric Solutions on Microsoft Azure
Modern Data Architecture on Azure: Design Data-centric Solutions on Microsoft Azure
Modern Data Analytics in Excel Using Power Query, Power Pivot, and More for Enhanced Data Analytics