AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. As an early adopter of large language model (LLM) technology, Zeta released Email Subject Line Generation in 2021.

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

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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.

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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.

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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.

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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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DagsHub

NOVEMBER 11, 2024

Many find themselves swamped by the volume and complexity of unstructured data. 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?

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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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Women in Big Data

NOVEMBER 27, 2024

By maintaining historical data from disparate locations, a data warehouse creates a foundation for trend analysis and strategic decision-making. Evaluate integration capabilities with existing data sources and Extract Transform and Load (ETL) tools. architecture for both structured and unstructured data.

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Pickl AI

JANUARY 28, 2025

Data Integration Once data is collected from various sources, it needs to be integrated into a cohesive format. Data Quality Management : Ensures that the integrated data is accurate, consistent, and reliable for analysis. They are useful for big data analytics where flexibility is needed.

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AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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ODSC - Open Data Science

OCTOBER 9, 2024

The rapid evolution of AI is transforming nearly every industry/domain, and software engineering is no exception. Well, the thing is that AI technologies are doing a few things. If you’re not leveraging AI yet, it’s time to start. At West, you’ll learn even more about AI’s role in reshaping software engineering.

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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. Interested in attending an ODSC event?

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phData

OCTOBER 17, 2024

Using 3rd party tooling is essential if you’re a Snowflake AI Data Cloud customer. Getting your data into Snowflake, creating analytics applications from the data, and even ensuring your Snowflake account runs smoothly all require some sort of tool. But you still want to start building out the data model.

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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

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

DECEMBER 2, 2024

In this blog, we will explain dataflows and their use cases and show an example of how to bring data from Snowflake AI Data Cloud into a dataflow. Most Power BI developers are familiar with Power Query , Which is the data transformation layer of Power BI. What are Dataflows, and Why are They So Great?

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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

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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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

JUNE 6, 2024

Composable CDP’s Traditionally, CDPs have been an out-of-the-box solution companies can buy and “plug and play” into their data infrastructure. These traditional CDPs are designed to gather and house their own data store—separate from the core data infrastructure.

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Pickl AI

JANUARY 15, 2025

They help stakeholders monitor performance at a glance and make timely decisions based on current data. ETL (Extract, Transform, Load) Tools ETL tools are crucial for data integration processes. Companies like Siemens leverage this tool for operational reporting and performance management across their global operations.

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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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ODSC - Open Data Science

APRIL 6, 2023

But its status as the go-between for programming and data professionals isn’t its only power. Within SQL you can also filter data, aggregate it and create valuations, manipulate data, update it, and even do data modeling. Data integration tools allow for the combining of data from multiple sources.

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DagsHub

OCTOBER 23, 2024

This article will discuss managing unstructured data for AI and ML projects. You will learn the following: Why unstructured data management is necessary for AI and ML projects. How to properly manage unstructured data. The different tools used in unstructured data management. What is Unstructured Data?

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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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Data Quality Data Lakes Data Warehouse Big Data 52

The MLOps Blog

MARCH 15, 2023

If you will ask data professionals about what is the most challenging part of their day to day work, you will likely discover their concerns around managing different aspects of data before they get to graduate to the data modeling stage. Provides data security using AI & blockchain technologies.

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Pickl AI

MARCH 3, 2025

Ensuring data accuracy and consistency through cleansing and validation processes. Data Analysis and Modelling Applying statistical techniques and analytical tools to identify trends, patterns, and anomalies. Developing data models to support analysis and reporting.

Business Intelligence 52

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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.

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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.

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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

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phData

JULY 18, 2023

The good news is that there’s a concept called the Modern Data Stack that when utilized properly, consistently helps empower organizations to harness the full potential of their data. Throughout this journey, we’ve helped hundreds of clients achieve eye-opening results by moving to the Modern Data Stack.

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phData

JULY 10, 2024

Unlike traditional BI tools, its user-friendly interface ensures that users of all technical levels can seamlessly interact with data. The platform’s integration with cloud data warehouses like Snowflake AI Data Cloud , Google BigQuery, and Amazon Redshift makes it a vital tool for organizations harnessing big data.

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phData

SEPTEMBER 27, 2024

Introduction: The Customer Data Modeling Dilemma You know, that thing we’ve been doing for years, trying to capture the essence of our customers in neat little profile boxes? For years, we’ve been obsessed with creating these grand, top-down customer data models. Yeah, that one.

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Pickl AI

JULY 18, 2024

MongoDB is a NoSQL database that uses a document-oriented data model. It stores data in flexible, JSON-like documents, allowing for dynamic schemas. Each document can have a different structure, allowing for flexibility in data modelling. What Is MongoDB? What Is a Document in MongoDB?

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Pickl AI

APRIL 22, 2025

Introduction A snowflake schema is a sophisticated data modeling technique used in data warehousing to efficiently organize and store large volumes of data. It is an extension of the star schema, designed to optimize storage, enhance data integrity, and support complex analytical queries.

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