Astera

JANUARY 11, 2023

Data modeling — which defines the database schema — is the heart of your data warehouse . After designing your data model, the next step is to generate a physical schema , which synchronizes your model with the target database. Now generating a new schema for the database is a complex task. Let’s see how this is done. .

Data Warehouse 52

Data Warehouse Data Modelling 52

Simplilearn

MAY 27, 2021

SQL (Structured Query Language) is a programming language used as an interface to manage databases.Various organizations use SQL systems to view and manipulate the information and data contained in their files, as well as to create and modify new tables. To truly comprehend SQL, it is essential to first understand what a database is. A database is.

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The Data Administration Newsletter

APRIL 3, 2024

I love writing this column for TDAN. It lets me discuss what I learned from a newly released data management book. When I publish a book through Technics Publications, I see the manuscript mostly through the eyes of a publisher. But when I write this column, I see the manuscript through the eyes of a […]

Data Modelling 52

Data Modelling Data Management 52

Smart Data Collective

AUGUST 28, 2021

Since data warehouses can deal only with structured data, they also require extract, transform, and load (ETL) processes to transform the raw data into a target structure ( Schema on Write ) before storing it in the warehouse. In other words, data warehouses store historical data that has been pre-processed to fit a relational schema.

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Data Warehouse Artificial Intelligence Data Management Planning 350

BI Insight

JULY 3, 2013

But, what if there are some other schemas other than “dbo” and some tables that are created in those schemas? from the code … Continue reading Drop tables from selected schemas database wide. The post Drop tables from selected schemas database wide appeared first on BI Insight. If we just delete “[dbo].”

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BI Insight

JULY 3, 2013

But, what if there are some other schemas other than “dbo” and some tables that are created in those schemas? from the code … Continue reading Drop tables from selected schemas database wide. The post Drop tables from selected schemas database wide appeared first on BI Insight. If we just delete “[dbo].”

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BI Insight

AUGUST 5, 2013

In this short post I’ll show you how to create database schema using dynamic SQL. The post How to create schema dynamically using dynamic SQL appeared first on BI Insight.

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BI Insight

AUGUST 5, 2013

In this short post I’ll show you how to create database schema using dynamic SQL. The post How to create schema dynamically using dynamic SQL appeared first on BI Insight.

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Simplilearn

DECEMBER 27, 2022

Fact tables and dimension tables are key components of a schema in a data warehouse. A fact table contains records that combine attributes from different dimension tables. These records allow users to analyze different aspects of their business, which can aid in decision-making and improving the business. Read More.

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Data Warehouse 235

Smart Data Collective

MARCH 29, 2022

But let’s back up a moment and first talk about the two most common types of data models or schema, found out there: stars and snowflakes. What are Star and Snowflake Schemas? In a star schema, aptly named for its configuration of a star-shape, the fact table is situated in the center. This would be the fact table.

Data Modelling 210

Data Modelling Data Analytics Data Analytics Digital 210

Dataversity

AUGUST 17, 2022

When setting up an Apache Cassandra table schema and anticipating how you’ll use the table, it’s a best practice to simultaneously formulate a thoughtful compaction strategy.

Data Modelling 245

Data Modelling 245

CMCrossroads

APRIL 22, 2024

This article explores some of the latest trends in agile development, including cloud-based infrastructure, online Scrum, containerization, DevOps, low-code/no-code tools, schema-less data, and serverless computing. Agile software development is constantly evolving to address the challenges of modern software development.

Agile 59

Agile 59

CMCrossroads

APRIL 22, 2024

This article explores some of the latest trends in agile development, including cloud-based infrastructure, online Scrum, containerization, DevOps, low-code/no-code tools, schema-less data, and serverless computing. Agile software development is constantly evolving to address the challenges of modern software development.

Agile 59

Agile 59

Simplilearn

MAY 10, 2021

When designing the database schema, integrity constraints are added. When authorized users make changes to the database, integrity constraints ensure that the data remains consistent. It defines constraints in SQL DDL commands such as 'CreateTable' and 'Alter Table.'

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Simplilearn

MAY 23, 2022

One of the most important characteristics of NoSQL databases like MongoDB is that they have no schema. It is different from other Relational Databases like MySQL and is very high-performance in nature. That is, unlike SQL, we do not specify a structure for the tables/datab. Read More.

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Documentation 130

Agile Connection

APRIL 22, 2024

This article explores some of the latest trends in agile development, including cloud-based infrastructure, online Scrum, containerization, DevOps, low-code/no-code tools, schema-less data, and serverless computing. Agile software development is constantly evolving to address the challenges of modern software development.

Agile 52

Agile 52

Agile Connection

APRIL 22, 2024

This article explores some of the latest trends in agile development, including cloud-based infrastructure, online Scrum, containerization, DevOps, low-code/no-code tools, schema-less data, and serverless computing. Agile software development is constantly evolving to address the challenges of modern software development.

Agile 52

Agile 52

Astera

DECEMBER 29, 2023

The structured format, commonly using star or snowflake schemas, enables you to navigate and analyze the data with ease. Data vault modeling combines elements from both the Third Normal Form (3NF) and star schema approaches to create a flexible and scalable data warehouse architecture. Each schema has its own advantages and trade-offs.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

The structured format, commonly using star or snowflake schemas, enables you to navigate and analyze the data with ease. Data vault modeling combines elements from both the Third Normal Form (3NF) and star schema approaches to create a flexible and scalable data warehouse architecture. Each schema has its own advantages and trade-offs.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

InfoQ Articles

AUGUST 23, 2023

modernizes NoSQL integration with advanced features, standardized specs (Jakarta NoSQL & Jakarta Data), enhanced queries, schema migration, and Quarkus framework compatibility. Eclipse JNoSQL 1.0.0 It simplifies NoSQL use, boosts performance, scalability, and integrates seamlessly.

Data Management 83

Data Management 83

Simplilearn

APRIL 3, 2021

Relational databases store data according to specific schemas. By contrast, NoSQL systems allow data to be stored using any structure required but provides a way for updating that data when changing that structure. What Is the Difference Between SQL and NoSQL?

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Astera

NOVEMBER 13, 2023

Enterprise Data Warehouse Schemas EDW schemas define how data is structured and stored within data warehousing systems. Let’s explore the three main types of schemas: 1. Star Schema: The star schema is a simple data organization structure used in data warehousing.

Data Warehouse 52

Data Warehouse E-Commerce Supply Chain Real-time Data 52

Simplilearn

JANUARY 16, 2022

Entity Framework has various features like LINQ queries, change tracking, updates, and schema migra. It provides an automated mechanism for developers. Microsoft made it available for development as part of the.NET framework. Read More.

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Astera

NOVEMBER 17, 2022

When we talk about data warehousing architectures, you have plenty of options, including 3NF, data vault, dimensional models (star and snowflake schema), and One Big Table (OBT). There are two types of schemas in dimensional models: star schema and snowflake schema. This problem is non-existent in a star schema.

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Management 52

Astera

MARCH 15, 2023

The language-neutral file format stores the schema in JSON , while the data itself is stored in a binary format, and both the data and the schema are stored in a single file or message to optimize the storage size. What sets Avro apart from other data file formats is schema evolution, meaning that it supports dynamic schemas.

Big Data 52

Big Data Data Quality Data Management 52

Simplilearn

DECEMBER 28, 2021

MongoDB Atlas has dynamic schemas which use JSON documents, and it acts as an alternative for table-type databases like SQL. MongoDB Atlas is a developer-oriented cloud service provided by MongoDB. It is open-source in nature and is a NoSQL database. Read More.

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Documentation 100

Astera

FEBRUARY 28, 2024

This process ensures the data is clean, accurate, and in harmony with the data warehouse schema. The data warehouse schema sets the rules, defining the structure with tables, columns, keys, and relationships. Leveraging the appropriate schema, such as star or snowflake schema can help optimize your data warehouse for reporting.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

InfoQ Articles

AUGUST 14, 2023

Specifically, it shows the GraphQL platform Netflix has built consisting of the Domain Graph Services framework for implementing GraphQL services in Java using Spring Boot and graphql-java, and tools for schema development. It also describes how the ecosystem has evolved at various stages of adoption. By Kavitha Srinivasan

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Astera

FEBRUARY 27, 2024

This process ensures the data is clean, accurate, and in harmony with the data warehouse schema. The data warehouse schema sets the rules, defining the structure with tables, columns, keys, and relationships. Leveraging the appropriate schema, such as star or snowflake can help optimize your data warehouse for reporting.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

FEBRUARY 27, 2024

This process ensures the data is clean, accurate, and in harmony with the data warehouse schema. The data warehouse schema sets the rules, defining the structure with tables, columns, keys, and relationships. Leveraging the appropriate schema, such as star or snowflake can help optimize your data warehouse for reporting.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

APRIL 27, 2023

Since it can hold relational and non-relational data, with undefined schema, in large volumes, you can do things like SQL queries and full-text searches; to uncover business insights. Data warehousing allows users to organize data using schema. Schemas are akin to folders. What is a Data Lake? What is a Data Warehouse?

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Data Warehouse Cloud Computing Data Management Data Governance 52

Astera

NOVEMBER 13, 2023

As far as the technical aspects are concerned, modern data warehouses do not follow a rigid schema, which means they can easily handle semi-structured and unstructured data. The traditional architecture is hence limited to ETL/ELT and mostly star schema. You may need to transform data to match the new schema requirements.

Data Warehouse 52

Data Warehouse Real-time Data Planning Agile 52

Astera

JANUARY 3, 2023

The denormalized star schema reduce s complexity and optimize s the maintenance of historical data, query performance, retrieval, and consumption for reporting. Let ’s see how aut omation simplifies complex data modeling tasks , e.g., defining and configuring dimensions and facts in a star schema. . Build a Dimension Model Feature.

Data Warehouse 52

Data Warehouse Data Modelling Business Intelligence Business Intelligence 52

BI Insight

MARCH 28, 2016

The database schema was NOT a proper star schema so there … Continue reading How to Define A Measure Table in Power BI Desktop. In this post I show you a simple trick to make your Power BI model more organised and more readable. I call it creating a “Measure Table”. Let me explain.

Business Intelligence 130

Business Intelligence Business Intelligence 130

Smart Data Collective

OCTOBER 20, 2021

It exists across cloud platforms and in different schemas (with multiple data dependencies). If legacy solutions are used, it will take a lot of time and effort; IT teams will be burdened with complex custom coding and EDI mapping, and tasks like data onboarding, data mapping , and data integration will take months to complete.

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Artificial Intelligence Big Data Data Modelling Data Management 309

Astera

MARCH 7, 2024

Data Source Identification and Validation In the next part of the ETL testing process, identify your source data and perform schema check s , table validation, and other initial checks. Applying Transformations Next, you must ensure that data is adequately transformed to match the destination data warehouse’s schema.

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Data Warehouse Data Quality Documentation Data Modelling 52

Astera

FEBRUARY 27, 2023

It’s a hybrid model that combines the benefits of Third Normal Form (3NF) and star schema architectures, making it a dream solution for data warehousing engineers. The data vault architecture is meant to be complementary to the star schema methodology of modeling your data warehouse. Data Vault 2.0

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Data Warehouse Data Modelling Visualization 40