Knowledge Hut

APRIL 23, 2024

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Big data offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

APRIL 23, 2024

Big data has revolutionized the world of data science altogether. With the help of big data analytics, we can gain insights from large datasets and reveal previously concealed patterns, trends, and correlations. Learn more about the 4 Vs of big data with examples by going for the Big Data certification online course.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Lyft Engineering

NOVEMBER 29, 2023

Druid at Lyft Apache Druid is an in-memory, columnar, distributed, open-source data store designed for sub-second queries on real-time and historical data. Druid enables low latency (real-time) data ingestion, flexible data exploration and fast data aggregation resulting in sub-second query latencies.

Kafka 104

Kafka Data Ingestion Datasets Architecture 104

Cloudera

AUGUST 26, 2021

In addition to big data workloads, Ozone is also fully integrated with authorization and data governance providers namely Apache Ranger & Apache Atlas in the CDP stack. While we walk through the steps one by one from data ingestion to analysis, we will also demonstrate how Ozone can serve as an ‘S3’ compatible object store.

Data Science 111

Data Science Cloud Hadoop Metadata 111

Rockset

JANUARY 30, 2024

With this architecture, users can separate ingestion compute from query compute, all while accessing the same real-time data. The memory optimized instance class is ideal for queries that process large datasets or have a large working set size due to the mix of queries. minutes to batch load the data.

Data Ingestion 64

Data Ingestion Utilities Architecture SQL 64

Data Engineering Weekly

MARCH 24, 2024

Moirai utilizes a large, diverse dataset and innovative techniques like any-variate attention and multiple patch-size projection layers to model complex, variable patterns. It addresses challenges across multiple domains and frequencies with zero-shot forecasting capabilities.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Cloudera

AUGUST 17, 2022

?. What if you could access all your data and execute all your analytics in one workflow, quickly with only a small IT team? CDP One is a new service from Cloudera that is the first data lakehouse SaaS offering with cloud compute, cloud storage, machine learning (ML), streaming analytics, and enterprise grade security built-in.

Cloud Computing 115

Cloud Computing Cloud Storage Data Science Government 115

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Engineering 92

Data Engineering Data Engineer Cloud Engineering 92

Towards Data Science

NOVEMBER 4, 2023

Indeed, datalakes can store all types of data including unstructured ones and we still need to be able to analyse these datasets. Indeed, why would we build a data connector from scratch if it already exists and is being managed in the cloud? You can change these # to conform to your data. Datalake example.

Data Engineering 82

Data Engineering Data Engineer Engineering BI 82

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. It supports ACID transactions and can run fast queries, typically through SQL commands, directly on object storage in the cloud or on-prem on structured and unstructured data.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. It supports ACID transactions and can run fast queries, typically through SQL commands, directly on object storage in the cloud or on-prem on structured and unstructured data.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

LinkedIn Engineering

DECEMBER 20, 2023

In content moderation classifier development, there are Data ETL (Export, Transform, Load) pipelines that collect data from various sources and store it in offline locations like a data lake or HDFS. Most of these steps are automated using the AutoML framework, saving data scientists’ time and reducing the risk of errors.

Machine Learning 90

Machine Learning Datasets Algorithm Architecture 90

ProjectPro

FEBRUARY 6, 2023

Global Availability Users can access Google Cloud Pub/Sub from anywhere in the world. Due to user control over message storage, the service can provide fast, global data access. For this project, you will require the COVID-19 Cases.csv dataset from data.world. the time it takes for a subscriber to get a published message.

Google Cloud 52

Google Cloud Cloud Cloud Storage Data Ingestion 52

Cloudyard

APRIL 4, 2024

Implementation: Implementation: We developed a Snowpark script to process customer transaction data stored in the Snowflake database. Data Ingestion: Reads customer transaction data from the “CUSTOMER_TRANSACTIONS” table in the Snowflake database. The script performs the following tasks: 1.Data

Retail 40

Retail Data Ingestion Metadata Datasets 40

Towards Data Science

MARCH 5, 2024

With on-demand pricing, you will generally have access to up to 2000 concurrent slots, shared among all queries in a single project, which is more than enough in most cases. Also, storage is much cheaper than compute and that means: With pre-joined datasets, you exchange compute for storage resources! So, which model should you choose?

Bytes 69

Bytes Google Cloud Cloud Storage Utilities 69

Knowledge Hut

DECEMBER 7, 2023

In today's data-driven world, the ability to transform raw data into meaningful insights is paramount, and Power BI empowers users to achieve just that. This article serves as your essential primer, offering a structured and accessible pathway to navigate the intricacies of Power BI.

BI 52

BI Raw Data Datasets Business Intelligence 52

Ascend.io

JANUARY 23, 2023

The new usage screens in this week’s release consolidate cost data for them, and provide instant access and visualization for the workloads over time. To that end, we are rolling out new features that provide the necessary transparency with which to manage costs, guide new investments, and focus tuning efforts.

Data Pipeline 52

Data Pipeline Data Ingestion Datasets Data 52

Ascend.io

JUNE 8, 2023

Acting as the core infrastructure, data pipelines include the crucial steps of data ingestion, transformation, and sharing. Data Ingestion Data in today’s businesses come from an array of sources, including various clouds, APIs, warehouses, and applications.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Rockset

MAY 31, 2023

Workload Isolation: When real-time data ingestion and query workloads run on the the same compute units, they directly compete for resources. When data ingestion has a flash flood moment, your queries will slow down or time out making your application flaky. Note the deep levels of nesting in these documents.

Data Ingestion 52

Data Ingestion Datasets Architecture Retail 52

Ascend.io

JUNE 6, 2023

After carefully examining our reference pipeline network, we’ve pinpointed four areas that play a critical role in driving cloud costs: Storage : When dealing with vast amounts of data, you need to store that data somewhere to be accessible for processing. Previously, each job was given its own container to run in.

Cloud 52

Cloud Data Pipeline Data Ingestion Cloud Storage 52

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. We’ll store the extracted data in a table.

Data Process 75

Data Process Process Raw Data Data 75

Precisely

MAY 13, 2024

A true enterprise-grade integration solution calls for source and target connectors that can accommodate: VSAM files COBOL copybooks open standards like JSON modern platforms like Amazon Web Services ( AWS ), Confluent , Databricks , or Snowflake Questions to ask each vendor: Which enterprise data sources and targets do you support?

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics. No wonder only 0.5

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Data Engineering Weekly

OCTOBER 30, 2022

Before you add another tool to your data stack, check out our latest guide for 10 things to consider when evaluating data observability platforms, including scalability, time to value, and ease of setup. The modern data stack is trying to address this problem in a silo; the org eventually has to tie everything to make it work.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Cloudera

DECEMBER 14, 2021

So to improve the speed of data analysis, the IRS worked with the combined technology integrating Cloudera Data Platform (CDP) and NVIDIA’s RAPIDS Accelerator for Apache Spark 3.0. The Roads and Transport Authority (RTA) operating in Dubai wanted to apply big data capabilities to transportation and enhance travel efficiency.

Transportation 110

Transportation Telecommunication Banking Data Lake 110

Knowledge Hut

JUNE 26, 2023

When screening resumes, most hiring managers prioritize candidates who have actual experience working on data engineering projects. Top Data Engineering Projects with Source Code Data engineers make unprocessed data accessible and functional for other data professionals. Which queries do you have?

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Data Engineering Podcast

MAY 29, 2022

Summary A large fraction of data engineering work involves moving data from one storage location to another in order to support different access and query patterns. With Select Star’s data catalog, a single source of truth for your data is built in minutes, even across thousands of datasets.

Architecture 100

Architecture Database Data Architecture PostgreSQL 100

Ascend.io

MAY 31, 2023

Table of Contents The Common Threads: Ingest, Transform, Share Before we explore the differences between the ETL process and a data pipeline , let’s acknowledge their shared DNA. Data Ingestion Data ingestion is the first step of both ETL and data pipelines.

Data Pipeline 52

Data Pipeline ETL Tools Pipeline-centric Data Warehouse 52

AltexSoft

AUGUST 29, 2023

Examples of unstructured data can range from sensor data in the industrial Internet of Things (IoT) applications, videos and audio streams, images, and social media content like tweets or Facebook posts. Data ingestion Data ingestion is the process of importing data into the data lake from various sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

APRIL 23, 2024

For example, talking about the history of big data in healthcare, hospitals faced many problems earlier in patient data management, security, and privacy. A hospital’s performance depends largely on how patient data is handled, including accessing and retrieving it for various purposes.

Big Data 52

Big Data Amazon Web Services Media Cloud Computing 52

Knowledge Hut

SEPTEMBER 26, 2023

Effective Data Storage: Azure Synapse offers robust data storage solutions that cater to the needs of modern data-driven organizations. It provides the infrastructure necessary for efficient data storage and management, enabling you to store and access large volumes of data reliably.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Data Engineering Weekly

NOVEMBER 20, 2022

Google AI: The Data Cards Playbook: A Toolkit for Transparency in Dataset Documentation Google published Data Cards , a dataset documentation framework aimed at increasing transparency across dataset lifecycles. link] The short YouTube video gives a nice overview of the Data Cards.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Monte Carlo

APRIL 24, 2023

In this article, we’ll dive deep into the data presentation layers of the data stack to consider how scale impacts our build versus buy decisions, and how we can thoughtfully apply our five considerations at various points in our platform’s maturity to find the right mix of components for our organizations unique business needs.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 100

Architecture Metadata Unstructured Data Machine Learning 100

Data Engineering Weekly

MARCH 5, 2023

The basics of the best practices are to establish Meta’s Ground Truth Maturity Framework [GTMF] [link] Google: Datasets at your fingertips in Google Search Easy access to the datasets is 80% of the problem solved in data engineering.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

ProjectPro

AUGUST 24, 2021

And if you are aspiring to become a data engineer, you must focus on these skills and practice at least one project around each of them to stand out from other candidates. Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Ascend.io

AUGUST 10, 2023

Technical Constraints Technical constraints pose another significant hurdle for data projects in a startup environment. These constraints include: Large Datasets: Startups generate a significant volume of data, from product features to log data. Their data engineering team consists of just one person.

Building 52

Building Data Pipeline Data Ingestion Datasets 52