Dataconomy

MARCH 20, 2025

Methods of creating data marts Let’s explain those methods. ETL processes ETL, or Extract, Transform, Load, plays a pivotal role in the creation of data marts. This process extracts data from various sources, transforms it into a desired format, and loads it into the data mart.

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Dataversity

MARCH 29, 2021

Have you ever been in a situation when you had to represent the ETL team by being up late for L3 support only to find out that one of your […]. The post Rethinking Extract Transform Load (ETL) Designs appeared first on DATAVERSITY.

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Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Choosing the right ETL tool is crucial for smooth data management.

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phData

SEPTEMBER 19, 2023

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Data modeling plays a pivotal role in defining the structure, relationships, and semantics of data within a data lake. Consistency of data throughout the data lake.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. This ensures data consistency and integrity.

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phData

OCTOBER 9, 2023

In this blog, we explore best practices and techniques to optimize Snowflake’s performance for data vault modeling , enabling your organizations to achieve efficient data processing, accelerated query performance, and streamlined ETL workflows.

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ODSC - Open Data Science

APRIL 6, 2023

It’s a foundational skill for working with relational databases Just about every data scientist or analyst will have to work with relational databases in their careers. So by learning to use SQL, you’ll write efficient and effective queries, as well as understand how the data is structured and stored.

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ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. in an enterprise data warehouse. What is a Datamart?

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Dataconomy

SEPTEMBER 4, 2023

Key features of cloud analytics solutions include: Data models , Processing applications, and Analytics models. Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence.

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Pickl AI

JUNE 28, 2023

Schema Integration Schema integration deals with reconciling data stored in different database schemas or structures. It involves mapping and transforming data elements to align with a unified schema. It requires human effort to extract data from each source and merge it.

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Pickl AI

JULY 3, 2023

It is the process of converting raw data into relevant and practical knowledge to help evaluate the performance of businesses, discover trends, and make well-informed choices. Data gathering, data integration, data modelling, analysis of information, and data visualization are all part of intelligence for businesses.

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Women in Big Data

NOVEMBER 27, 2024

It consolidates data from various systems, such as transactional databases, CRM platforms, and external data sources, enabling organizations to perform complex queries and derive insights. Evaluate integration capabilities with existing data sources and Extract Transform and Load (ETL) tools.

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Mlearning.ai

MAY 16, 2023

This article discusses five commonly used architectural design patterns in data engineering and their use cases. ETL Design Pattern The ETL (Extract, Transform, Load) design pattern is a commonly used pattern in data engineering. Finally, the transformed data is loaded into the target system.

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phData

SEPTEMBER 26, 2023

Sources The sources involved could influence or determine the options available for the data ingestion tool(s). These could include other databases, data lakes, SaaS applications (e.g. Salesforce), Access databases, SharePoint, or Excel spreadsheets. Data flows from the current data platform to the destination.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

An example direct acyclic graph (DAG) might automate data ingestion, processing, model training, and deployment tasks, ensuring that each step is run in the correct order and at the right time. Though it’s worth mentioning that Airflow isn’t used at runtime as is usual for extract, transform, and load (ETL) tasks.

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Pickl AI

MARCH 19, 2025

Without data engineering , companies would struggle to analyse information and make informed decisions. What Does a Data Engineer Do? A data engineer creates and manages the pipelines that transfer data from different sources to databases or cloud storage. How is Data Engineering Different from Data Science?

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Pickl AI

JANUARY 28, 2025

They encompass all the origins from which data is collected, including: Internal Data Sources: These include databases, enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and flat files within an organization. Data can be structured (e.g., databases), semi-structured (e.g.,

Business Intelligence 52

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Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

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Pickl AI

JUNE 11, 2024

Summary: A data warehouse is a central information hub that stores and organizes vast amounts of data from different sources within an organization. Unlike operational databases focused on daily tasks, data warehouses are designed for analysis, enabling historical trend exploration and informed decision-making.

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Dataconomy

OCTOBER 17, 2023

People who desire to work with big data have to comprehend the architecture of the data warehouse because it helps them understand that they deal with various parts that make up the whole data warehouse. But It’s always better to call data warehouse experts before making a big decision.

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phData

SEPTEMBER 25, 2024

With the importance of data in various applications, there’s a need for effective solutions to organize, manage, and transfer data between systems with minimal complexity. While numerous ETL tools are available on the market, selecting the right one can be challenging. What is Fivetran?

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Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Warehousing: Amazon Redshift, Google BigQuery, etc.

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phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. This is where Fivetran and the Modern Data Stack come in.

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phData

MAY 11, 2023

With the “Data Productivity Cloud” launch, Matillion has achieved a balance of simplifying source control, collaboration, and dataops by elevating Git integration to a “first-class citizen” within the framework. In Matillion ETL, the Git integration enables an organization to connect to any Git offering (e.g.,

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Pickl AI

JANUARY 15, 2025

These tools enable organizations to convert raw data into actionable insights through various means such as reporting, analytics, data visualization, and performance management. Data Processing: Cleaning and organizing data for analysis.

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Pickl AI

MARCH 3, 2025

Essentially, BI bridges the gap between raw data and actionable knowledge. It gathers information from various sources sales databases, marketing platforms, customer feedback, and more and consolidates it into a unified view. Ensuring data accuracy and consistency through cleansing and validation processes.

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Dataconomy

MARCH 24, 2023

Some of the common career opportunities in BI include: Entry-level roles Data analyst:  A data analyst is responsible for collecting and analyzing data, creating reports, and presenting insights to stakeholders. They may also be involved in data modeling and database design.

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Dataconomy

MARCH 24, 2023

Some of the common career opportunities in BI include: Entry-level roles Data analyst:  A data analyst is responsible for collecting and analyzing data, creating reports, and presenting insights to stakeholders. They may also be involved in data modeling and database design.

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Pickl AI

AUGUST 9, 2024

Hierarchies align data modelling with business processes, making it easier to analyse data in a context that reflects real-world operations. Designing Hierarchies Designing effective hierarchies requires careful consideration of the business requirements and the data model.

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DagsHub

NOVEMBER 11, 2024

In this article, we’ll explore how AI can transform unstructured data into actionable intelligence, empowering you to make informed decisions, enhance customer experiences, and stay ahead of the competition. What is Unstructured Data? Word2Vec , GloVe , and BERT are good sources of embedding generation for textual data.

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Precisely

MARCH 9, 2023

Processing speeds were considerably slower than they are today, so large volumes of data called for an approach in which data was staged in advance, often running ETL (extract, transform, load) processes overnight to enable next-day visibility to key performance indicators. They are malleable.

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phData

DECEMBER 2, 2024

It allows a developer to perform routine ETL tasks in a low-code/no-code environment using drag-and-drop tools or custom M-Code. Second, it drives up consumption or compute resources in your database. Dataflows are one of the data products that can be created in Fabric’s Power BI workload.

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Pickl AI

APRIL 6, 2023

Understand the fundamentals of data engineering: To become an Azure Data Engineer, you must first understand the concepts and principles of data engineering. Knowledge of data modeling, warehousing, integration, pipelines, and transformation is required. What are Data Masking features available in Azure?

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phData

JUNE 27, 2023

The modern data stack (MDS) has seen massive changes over the past few decades, fueled by technological advances and new platforms. As a result, we are presented with specialized data platforms, databases, and warehouses. Platform and More dbt is a database deployment & development platform. Proceed as you see fit.

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phData

JULY 11, 2023

Power BI Datamarts provides a low/no code experience directly within Power BI Service that allows developers to ingest data from disparate sources, perform ETL tasks with Power Query, and load data into a fully managed Azure SQL database. Expand the databases and schemas to show the associated tables.

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IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

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phData

APRIL 20, 2023

Hashed PKs were introduced as a means of eliminating the bottleneck encountered by most database sequence generators, making this DV pattern ideal for customers prioritizing data loading performance and using data warehouse automation tools. Again dbt Data Vault package automates a major portion of it.

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