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.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

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. Big Data Technologies: Hadoop, Spark, etc. Read more to know.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

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.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

ODSC - Open Data Science

APRIL 6, 2023

For budding data scientists and data analysts, there are mountains of information about why you should learn R over Python and the other way around. Though both are great to learn, what gets left out of the conversation is a simple yet powerful programming language that everyone in the data science world can agree on, SQL.

SQL 98

SQL Data Scientist Database Data Science 98

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. Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

ODSC - Open Data Science

SEPTEMBER 27, 2023

In contrast, data warehouses and relational databases adhere to the ‘Schema-on-Write’ model, where data must be structured and conform to predefined schemas before being loaded into the database. Schema Enforcement: Data warehouses use a “schema-on-write” approach. You can connect with her on Linkedin.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

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.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

ODSC - Open Data Science

JANUARY 11, 2024

Getting Started with AI in High-Risk Industries, How to Become a Data Engineer, and Query-Driven Data Modeling How To Get Started With Building AI in High-Risk Industries This guide will get you started building AI in your organization with ease, axing unnecessary jargon and fluff, so you can start today. Register here!

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

JUNE 28, 2023

Limited Scalability : The process is not workable for handling large volumes of data. ETL (Extract, Transform, Load) ETL is a widely used data integration technique. Pros Automation: ETL tools automate the extraction, transformation, and loading processes. Thereby, improving data quality and consistency.

Data Mining 52

Data Mining Data Mining Data Mining ETL 52

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?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

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.

Data Warehouse 103

Data Warehouse Big Data Big Data ETL 103

phData

SEPTEMBER 26, 2023

Data flows from the current data platform to the destination. Transformations Transformations can be a part of data ingestion (ETL pattern) or can take place at a later stage after data has been landed (ELT pattern). Either way, it’s important to understand what data is transformed, and how so.

SQL 52

SQL Database ETL Data Modeling 52

phData

JULY 17, 2023

In order to fully leverage this vast quantity of collected data, companies need a robust and scalable data infrastructure to manage it. This is where Fivetran and the Modern Data Stack come in. Data modeling, data cleanup, etc. With easily scalable cloud data warehouses, this is no longer an issue.

Data Warehouse 52

Data Warehouse Data Pipeline Cloud Data ETL 52

ODSC - Open Data Science

OCTOBER 9, 2024

What should you be looking for?

Apache Kafka 40

Apache Kafka AI AI Machine Learning 40

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.

Data Warehouse 52

Data Warehouse Data Quality ETL Business Intelligence 52

Alation

OCTOBER 27, 2022

We specialize in multiple functions, which include but are not limited to, data governance , dashboarding, data & analytics engineering, and data science. At Alation, we focus most of our time on connecting data sources and building useful data transformations to provide reporting for different teams.

Data Analyst 52

Data Analyst Data Scientist Analytics Analytics 52

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.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

phData

OCTOBER 17, 2024

Apache Airflow Airflow is an open-source ETL software that is very useful when paired with Snowflake. By leveraging version control, testing, and documentation features, dbt Core enables teams to ensure data quality and consistency across their pipelines while integrating seamlessly with modern data warehouses.

AI 52

AI AI SQL Data Quality 52

AWS Machine Learning Blog

AUGUST 21, 2023

The capabilities of Lake Formation simplify securing and managing distributed data lakes across multiple accounts through a centralized approach, providing fine-grained access control. Solution overview We demonstrate this solution with an end-to-end use case using a sample dataset, the TPC data model.

AWS 92

AWS Data Lakes Clustering Data Preparation 92

Pickl AI

AUGUST 11, 2024

These tools enable effective data structuring, transformation, and analysis, supporting best practices for dimensional modelling and ensuring high-quality, consistent business metrics. These tools help streamline the design process and ensure consistency.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

Pickl AI

JULY 18, 2024

Read Blogs: Crucial Statistics Interview Questions for Data Science Success. MongoDB is a NoSQL database that handles large-scale data and modern application requirements. Unlike traditional relational databases, MongoDB stores data in flexible, JSON-like documents, allowing for dynamic schemas. What is MongoDB?

Database 52

Database SQL Data Analyst Database Administration 52

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.

AWS 111

AWS Machine Learning Machine Learning ML 111

Pickl AI

JUNE 11, 2024

Let’s delve into the key components that form the backbone of a data warehouse: Source Systems These are the operational databases, CRM systems, and other applications that generate the raw data feeding the data warehouse. Data Extraction, Transformation, and Loading (ETL) This is the workhorse of architecture.

Data Warehouse 52

Data Warehouse ETL Data Mining Data Mining 52

phData

JULY 18, 2023

Slow Response to New Information: Legacy data systems often lack the computation power necessary to run efficiently and can be cost-inefficient to scale. This typically results in long-running ETL pipelines that cause decisions to be made on stale or old data.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

Pickl AI

MARCH 19, 2025

Learning these tools is crucial for building scalable data pipelines. offers Data Science courses covering these tools with a job guarantee for career growth. Introduction Imagine a world where data is a messy jungle, and we need smart tools to turn it into useful insights.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52