Aggregated Data, Architecture and Raw Data

Complete Guide to Data Transformation: Basics to Advanced

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

Raw Data Datasets Aggregated Data Data Pipeline

Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?

Data Pipeline

Data Pipeline Architecture Kafka AWS

Building a large scale unsupervised model anomaly detection system?—?Part 1

Lyft Engineering

APRIL 21, 2023

In a previous blog post , we explored the architecture and challenges of the platform. However, consuming this raw data presents several pain points: The number of requests varies across models; some receive a large number of requests, while others receive only a few.

Systems

Systems Building Machine Learning Datasets

Webinars

Agent Tooling: Connecting AI to Your Tools, Systems & Data

How to Modernize Manufacturing Without Losing Control

Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

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Consulting Case Study: Job Market Analysis

WeCloudData

OCTOBER 19, 2021

Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.

Consulting

Consulting Raw Data Data Lake Data Pipeline

Consulting Case Study: Job Market Analysis

WeCloudData

OCTOBER 19, 2021

Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.

Consulting

Consulting Raw Data Data Lake Data Pipeline

Tips to Build a Robust Data Lake Infrastructure

DareData

JULY 5, 2023

If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. For example, an industrial analytics team wants to use the logs from raw data. Understanding the Architecture No company is alike and no infrastructure will be alike.

Data Lake

Data Lake Building Raw Data ETL Tools

Rollups on Streaming Data: Rockset vs Apache Druid

Rockset

AUGUST 25, 2021

They are an essential part of the modern data stack for powering: Real-time search applications Social features in the product Recommendation/rewards features in the product Real-time dashboards IoT applications These use cases can have several TBs per day streaming in - they are literally data torrents.

Aggregated Data

Aggregated Data Hadoop SQL Data Lake

Data Lake vs. Data Warehouse: Differences and Similarities

U-Next

SEPTEMBER 7, 2022

Autonomous data warehouse from Oracle. . What is Data Lake? . Essentially, a data lake is a repository of raw data from disparate sources. A data lake stores current and historical data similar to a data warehouse. Atlas Data Lake powered by MongoDB. . Synapse on Microsoft Azure. .

Data Lake

Data Lake Data Warehouse Unstructured Data Amazon Web Services

AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

FEBRUARY 8, 2023

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. How Does AWS Glue Work?

AWS

AWS Scala Metadata Data Lake

ELT Explained: What You Need to Know

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems. What Is ELT? So, what exactly is ELT?

Raw Data

Raw Data Data Warehouse Data Cleanse Data Integration

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it. Modern data stack architecture.

IT

IT Data Warehouse Data Governance Data Lake

Using Metrics Layer to Standardize and Scale Experimentation at DoorDash

DoorDash Engineering

APRIL 12, 2023

These steps ensure that our data is always up-to-date and complete. Most of the inferences in our stats engine are performed using the Delta method which operates directly on moment aggregates at the experiment level. Thus, it is crucial to strike a balance between pre-aggregation and flexibility.

SQL

SQL Metadata Raw Data Government

Observability Platforms: 8 Key Capabilities and 6 Notable Solutions

Databand.ai

JULY 10, 2023

Observability platforms not only supply raw data but also offer actionable insights through visualizations, dashboards, and alerts. With the widespread adoption of microservices architectures, teams face greater challenges in achieving full observability for their systems and resolving issues promptly.

Data Pipeline

Data Pipeline Algorithm Data Engineering Raw Data

20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. This big data project discusses IoT architecture with a sample use case.

Data Engineering

Data Engineering Data Engineer Coding Project

100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

JULY 27, 2021

Below are some big data interview questions for data engineers based on the fundamental concepts of big data, such as data modeling, data analysis , data migration, data processing architecture, data storage, big data analytics, etc.

Data Engineering

Data Engineering Data Engineer Engineering Hadoop

Handling Out-of-Order Data in Real-Time Analytics Applications

Rockset

APRIL 15, 2022

These real- and near-real-time use cases dramatically narrow the time windows for both data freshness and query speeds while amping up the risk for data errors. Rockset not only continuously ingests data, but also can “rollup” the data as it is being generated.

Analytics Application

Analytics Application Data Warehouse Kafka Raw Data

Data Engineering Digest

Complete Guide to Data Transformation: Basics to Advanced

Data Pipeline- Definition, Architecture, Examples, and Use Cases

Webinars

Trending Sources

Building a large scale unsupervised model anomaly detection system?—?Part 1

Webinars

Consulting Case Study: Job Market Analysis

Consulting Case Study: Job Market Analysis

Tips to Build a Robust Data Lake Infrastructure

Rollups on Streaming Data: Rockset vs Apache Druid

Data Lake vs. Data Warehouse: Differences and Similarities

AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ELT Explained: What You Need to Know

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

Using Metrics Layer to Standardize and Scale Experimentation at DoorDash

Observability Platforms: 8 Key Capabilities and 6 Notable Solutions

20+ Data Engineering Projects for Beginners with Source Code

100+ Data Engineer Interview Questions and Answers for 2023

Handling Out-of-Order Data in Real-Time Analytics Applications

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