ProjectPro

JUNE 6, 2025

From handling missing values to merging datasets and performing advanced transformations, our cheatsheet will equip you with the skills needed to unleash the full potential of the Pandas library in real-world data analysis projects. Loading data into a DataFrame Here, you will explore different methods to load external data into a DataFrame.

Data Process 40

Data Process Process Aggregated Data Data Science 40

Towards Data Science

NOVEMBER 16, 2023

Data Management A tutorial on how to use VDK to perform batch data processing Photo by Mika Baumeister on Unsplash Versatile Data Ki t (VDK) is an open-source data ingestion and processing framework designed to simplify data management complexities.

Data Process 98

Data Process Process Raw Data Data 98

Netflix Tech

MAY 9, 2025

At Netflix, we embarked on a journey to build a robust event processing platform that not only meets the current demands but also scales for future needs. This blog post delves into the architectural evolution and technical decisions that underpin our Ads event processing pipeline.

Process 73

Process Building Metadata Kafka 73

Snowflake

JUNE 10, 2025

For years, Snowflake has been laser-focused on reducing these complexities, designing a platform that streamlines organizational workflows and empowers data teams to concentrate on what truly matters: driving innovation. This native integration streamlines development and accelerates the delivery of transformed data.

Data Pipeline 89

Data Pipeline SQL Python Building 89

Monte Carlo

NOVEMBER 12, 2024

A data engineering architecture is the structural framework that determines how data flows through an organization – from collection and storage to processing and analysis. It’s the big blueprint we data engineers follow in order to transform raw data into valuable insights.

Architecture 96

Architecture Data Engineer Data Engineering Engineering 96

The Pragmatic Engineer

OCTOBER 17, 2024

Code and raw data repository:   Version control: GitHub Heavily using GitHub Actions for things like getting warehouse data from vendor APIs, starting cloud servers, running benchmarks, processing results, and cleaning up after tuns. Internal comms: Chat: Slack Coordination / project management: Linear 3.

Cloud 336

Cloud Metadata AWS Cloud Computing 336

AltexSoft

AUGUST 25, 2021

And this technology of Natural Language Processing is available to all businesses. Available methods for text processing and which one to choose. Specifics of data used in NLP. What is Natural Language Processing? Here are some big text processing types and how they can be applied in real life. Main NLP use cases.

Process 139

Process Deep Learning Datasets Machine Learning 139

ThoughtSpot

JUNE 2, 2025

For data analysts and engineers, the journey from raw data to actionable business insights for business users is never as simple as it sounds. The semantic layer is a critical component in this process, serving as the bridge between complex data sources and the business logic required for informed decision-making.

Raw Data 64

Raw Data Government Algorithm Data 64

ProjectPro

JUNE 6, 2025

Welcome to the world of Machine Learning, where we will discover how machines learn from data, make predictions and decisions like magic. From Python coding to real-world AI applications, let us dive in and demystify the machine learning process together. Table of Contents Machine Learning Process: How Does Machine Learning Work?

Machine Learning 40

Machine Learning Process Entertainment Algorithm 40

Christophe Blefari

MARCH 1, 2023

In the ELT, the load is done before the transform part without any alteration of the data leaving the raw data ready to be transformed in the data warehouse. In a simple words dbt sits on top of your raw data to organise all your SQL queries that are defining your data assets.

Data Warehouse 278

Data Warehouse SQL Metadata Raw Data 278

Cloudyard

JANUARY 15, 2025

Read Time: 2 Minute, 33 Second Snowflakes PARSE_DOCUMENT function revolutionizes how unstructured data, such as PDF files, is processed within the Snowflake ecosystem. However, Ive taken this a step further, leveraging Snowpark to extend its capabilities and build a complete data extraction process. Why Use PARSE_DOC?

Data Cleanse 52

Data Cleanse Insurance Raw Data Unstructured Data 52

Cloudera

DECEMBER 4, 2024

Today enterprises can leverage the combination of Cloudera and Snowflake—two best-of-breed tools for ingestion, processing and consumption of data—for a single source of truth across all data, analytics, and AI workloads.

AWS 89

AWS Raw Data Relational Database Government 89

Ascend.io

OCTOBER 28, 2024

What is Data Transformation? Data transformation is the process of converting raw data into a usable format to generate insights. It involves cleaning, normalizing, validating, and enriching data, ensuring that it is consistent and ready for analysis.

Raw Data 52

Raw Data Aggregated Data Data Pipeline Data Validation 52

Cloudyard

DECEMBER 24, 2024

In this blog, well explore Building an ETL Pipeline with Snowpark by simulating a scenario where commerce data flows through distinct data layersRAW, SILVER, and GOLDEN.These tables form the foundation for insightful analytics and robust business intelligence. They need to: Consolidate raw data from orders, customers, and products.

Building 52

Building Raw Data Scala Java 52

ProjectPro

JUNE 6, 2025

Cloud computing is the future, given that the data being produced and processed is increasing exponentially. As per the March 2022 report by statista.com, the volume for global data creation is likely to grow to more than 180 zettabytes over the next five years, whereas it was 64.2 zettabytes in 2020.

AWS 67

AWS Big Data SQL Raw Data 67

Analytics Vidhya

FEBRUARY 25, 2023

The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Cloud Storage 162

Cloud Storage Data Lake Cloud Unstructured Data 162

KDnuggets

JUNE 12, 2025

It will be used to extract the text from PDF files LangChain: A framework to build context-aware applications with language models (we’ll use it to process and chain document tasks). It will be used to process and organize the text properly. View full parsed raw data") print("2. View full parsed raw data 2.

Building 57

Building Metadata Raw Data Data Science 57

Snowflake

NOVEMBER 11, 2024

Here’s how Snowflake Cortex AI and Snowflake ML are accelerating the delivery of trusted AI solutions for the most critical generative AI applications: Natural language processing (NLP) for data pipelines: Large language models (LLMs) have a transformative potential, but they often batch inference integration into pipelines, which can be cumbersome.

Unstructured Data 98

Unstructured Data SQL AWS Healthcare 98

Teradata

MAY 30, 2025

Mohan Talla May 30, 2025 11 min read Building and orchestrating a new data pipeline can feel daunting. Fortunately, Teradata offers integrations to many modular tools that facilitate routine processes allowing data engineers to focus on high-value tasks such as governance, data quality, and efficiency. dagster-dbt==0.23.9

Data Integration 52

Data Integration Raw Data Metadata Data Pipeline 52

ProjectPro

JUNE 6, 2025

Today, data engineers are constantly dealing with a flood of information and the challenge of turning it into something useful. The journey from raw data to meaningful insights is no walk in the park. It requires a skillful blend of data engineering expertise and the strategic use of tools designed to streamline this process.

Data Pipeline 49

Data Pipeline Google Cloud AWS Kafka 49

ProjectPro

JUNE 6, 2025

All the data preparation steps for machine learning algorithms implementation will be covered along with tools. Table of Contents What is Data Preparation for Machine Learning? Data preparation is usually the first step when one tries to solve real-world problems using ML. csv", which is compatible with data analytics tools.

Data Preparation 45

Data Preparation Machine Learning Project IT 45

ProjectPro

JUNE 6, 2025

However, the modern data ecosystem encompasses a mix of unstructured and semi-structured data—spanning text, images, videos, IoT streams, and more—these legacy systems fall short in terms of scalability, flexibility, and cost efficiency. That’s where data lakes come in.

Data Lake 40

Data Lake Building Hadoop Raw Data 40

ProjectPro

JUNE 6, 2025

Want to process peta-byte scale data with real-time streaming ingestions rates, build 10 times faster data pipelines with 99.999% reliability, witness 20 x improvement in query performance compared to traditional data lakes, enter the world of Databricks Delta Lake now.

Data Lake 63

Data Lake Data Warehouse Metadata Unstructured Data 63

Hevo

DECEMBER 6, 2024

Data preparation tools are very important in the analytics process. They transform raw data into a clean and structured format ready for analysis. These tools simplify complex data-wrangling tasks like cleaning, merging, and formatting, thus saving precious time for analysts and data teams. 

Data Preparation 52

Data Preparation Raw Data Data Process 52

ProjectPro

JUNE 6, 2025

We will now describe the difference between these three different career titles, so you get a better understanding of them: Data Engineer A data engineer is a person who builds architecture for data storage. They can store large amounts of data in data processing systems and convert raw data into a usable format.

Engineering 75

Engineering Software Engineer Software Engineering Deep Learning 75

Cloudera

JANUARY 9, 2025

AI today involves ML, advanced analytics, computer vision, natural language processing, autonomous agents, and more. It means combining data engineering, model ops, governance, and collaboration in a single, streamlined environment. Beyond Buzzwords: Real Results We know AI can sound like hype.

Machine Learning 85

Machine Learning Raw Data Government Algorithm 85

ProjectPro

JUNE 6, 2025

Data engineering is the foundation for data science and analytics by integrating in-depth knowledge of data technology, reliable data governance and security, and a solid grasp of data processing. Data engineers need to meet various requirements to build data pipelines.

AWS 52

AWS Data Engineer Data Engineering Project 52

ProjectPro

JUNE 6, 2025

But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses.

AWS 66

AWS Scala Metadata Data Lake 66

DataKitchen

DECEMBER 6, 2024

Would you like help maintaining high-quality data across every layer of your Medallion Architecture? Like an Olympic athlete training for the gold, your data needs a continuous, iterative process to maintain peak performance.

Architecture 52

Architecture Raw Data High Quality Data Data Validation 52

Engineering at Meta

JANUARY 21, 2025

Strobelight is also not a single profiler but an orchestrator of many different profilers (even ad-hoc ones) that runs on all production hosts at Meta, collecting detailed information about CPU usage, memory allocations, and other performance metrics from running processes.

Technology 115

Technology Metadata Utilities Engineering 115

ProjectPro

JUNE 6, 2025

It starts with data selection from one or more data sources, then moves on to data transformation within a staging framework. Finally, you can store the collected and altered data in a warehouse for storage and analysis. It consists of extracting data and loading it into the target server/data warehouse in its raw form.

Data Engineer 40

Data Engineer Data Engineering Engineering Data Lake 40

Cloudyard

MAY 4, 2025

This combination streamlines ETL processes, increases flexibility, and reduces manual coding. In this blog, I walk you through a use case where DBT orchestrates an automated S3-to-Snowflake ingestion flow using Snowflake capabilities like file handling, schema inference, and data loading. But Isnt DBT Just for Transformations?

ETL Tools 59

ETL Tools Raw Data SQL Python 59

Edureka

MAY 27, 2025

The architecture of Microsoft Fabric is based on several essential elements that work together to simplify data processes: 1. OneLake Data Lake OneLake provides a centralized data repository and is the fundamental storage layer of Microsoft Fabric. Transform Your Data Analytics with Microsoft Fabric!

Architecture 52

Architecture BI Business Intelligence Data Lake 52

ProjectPro

JUNE 6, 2025

As she deals with vast amounts of data from multiple sources, Emily seeks a solution to transform this raw data into valuable insights. Emily can efficiently process, clean, and transform data by seamlessly merging dbt's data transformation features with Snowflake's scalable cloud data warehouses. "dbt

Pipeline-centric 40

Pipeline-centric Database-centric Raw Data Data Warehouse 40

ProjectPro

JUNE 6, 2025

Most of us have observed that data scientist is usually labeled the hottest job of the 21st century, but is it the only most desirable job? No, that is not the only job in the data world. Store the data in in Google Cloud Storage to ensure scalability and reliability.

Data Engineer 59

Data Engineer Data Engineering Project Engineering 59

ProjectPro

JUNE 6, 2025

Building data pipelines is a core skill for data engineers and data scientists as it helps them transform raw data into actionable insights. You’ll walk through each stage of the data processing workflow, similar to what’s used in production-grade systems. Python fits that role perfectly.

Python 40

Python Building PostgreSQL Raw Data 40

ProjectPro

JUNE 6, 2025

Over the years, individuals and businesses have continuously become data-driven. The urge to implement data-driven insights into business processes has consequently increased the data volumes involved. Open source tools like Apache Airflow have been developed to cope with the challenges of handling voluminous data.

Data Pipeline 45

Data Pipeline Building Data Lake Raw Data 45