Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Ingestion layer 2.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. Benjamin Kennedy, Cloud Solutions Architect at Striim, emphasizes the outcome-driven nature of data pipelines.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Cloudera

NOVEMBER 1, 2023

And so we are thrilled to introduce our latest applied ML prototype (AMP) — a large language model (LLM) chatbot customized with website data using Meta’s Llama2 LLM and Pinecone’s vector database. High-level overview of real-time data ingest with Cloudera DataFlow to Pinecone vector database.

Machine Learning 109

Machine Learning Data Ingestion Database Architecture 109

Snowflake

NOVEMBER 19, 2024

Ongoing data uploads While one-time uploads can be managed using the solutions discussed above, customers must also consider how to handle new data generated on a daily basis. How Snowflake can help: Snowflake offers a variety of options for data ingestion. This approach helps optimize storage costs.

Cloud 60

Cloud Data Ingestion Data Validation Data Security 60

Snowflake

APRIL 18, 2024

Legacy SIEM cost factors to keep in mind Data ingestion: Traditional SIEMs often impose limits to data ingestion and data retention. Snowflake allows security teams to store all their data in a single platform and maintain it all in a readily accessible state, with virtually unlimited cloud data storage capacity.

Data Lake 83

Data Lake Data Ingestion Bytes Cloud Computing 83

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

Christophe Blefari

JANUARY 20, 2024

formats — This is a huge part of data engineering. Picking the right format for your data storage. The main difference between both is the fact that your computation resides in your warehouse with SQL rather than outside with a programming language loading data in memory. workflows (Airflow, Prefect, Dagster, etc.)

Data Engineer 130

Data Engineer Data Engineering Engineering Hadoop 130

Knowledge Hut

SEPTEMBER 26, 2023

This is particularly valuable in today's data landscape, where information comes in various shapes and sizes. Effective Data Storage: Azure Synapse offers robust data storage solutions that cater to the needs of modern data-driven organizations. Key Features of Databricks 1.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. As a certified Azure Data Engineer, you have the skills and expertise to design, implement and manage complex data storage and processing solutions on the Azure cloud platform.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

Snowflake

NOVEMBER 29, 2023

For example, the data storage systems and processing pipelines that capture information from genomic sequencing instruments are very different from those that capture the clinical characteristics of a patient from a site. A conceptual architecture illustrating this is shown in Figure 3.

Metadata 88

Metadata Healthcare Medical Data Storage 88

Cloudera

AUGUST 9, 2022

Customers, especially those in regulated industries with strict data protection and compliance requirements, routinely ask a straightforward question of our technical strategy experts: what should I do if a catastrophe hits my business and threatens to take out my data platform? The CDP Disaster Recovery Reference Architecture.

Data Lake 77

Data Lake Data Warehouse Architecture Data Ingestion 77

Cloudera

APRIL 26, 2023

Can you achieve similar outcomes with your on-premises data platform? Application modernization initiatives have led to cloud native architectures gaining popularity on premises, making it a sensible choice to extend to your data platform. This is exactly where cloud native architectures excel, and why they are so popular.

Cloud 63

Cloud Building Utilities Architecture 63

Knowledge Hut

APRIL 23, 2024

The history of big data takes people on an astonishing journey of big data evolution, tracing the timeline of big data. The Emergence of Data Storage and Processing Technologies A data storage facility first appeared in the form of punch cards, developed by Basile Bouchon to facilitate pattern printing on textiles in looms.

Big Data 52

Big Data Amazon Web Services Cloud Computing Media 52

Knowledge Hut

NOVEMBER 2, 2023

They work with various Azure services and tools to build scalable, efficient, and reliable data pipelines, data storage solutions, and data processing systems. Azure Data Engineer vs Azure Devops: Project Involvement Data Engineers are involved in projects related to data ingestion, transformation, storage, and analytics.

Data Engineer 52

Data Engineer Data Engineering Engineering Pipeline-centric 52

Towards Data Science

DECEMBER 1, 2023

Technical Overview The project architecture is depicted as follows: Google Calendar -> Fivetran -> Snowflake -> dbt -> Snowflake Dashboard , with GitHub Actions orchestrating the deployment. Storage —  Snowflake Snowflake, a cloud-based data warehouse tailored for analytical needs, will serve as our data storage solution.

Data Engineer 68

Data Engineer Data Engineering Project Engineering 68

RandomTrees

SEPTEMBER 6, 2020

Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS). Built on new SQL database engine, it provides a unique architecture designed for the cloud.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Cloudera

FEBRUARY 8, 2021

Future connected vehicles will rely upon a complete data lifecycle approach to implement enterprise-level advanced analytics and machine learning enabling these advanced use cases that will ultimately lead to fully autonomous drive.

Manufacturing 107

Manufacturing Machine Learning Data Ingestion Electronics 107

Knowledge Hut

MARCH 28, 2024

Job Role 1: Azure Data Engineer Azure Data Engineers develop, deploy, and manage data solutions with Microsoft Azure data services. They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

Databand.ai

JUNE 28, 2023

They’re betting their business on it and that the data pipelines that run it will continue to work. Context is crucial (and often lacking) A major cause of data quality issues and pipeline failures are transformations within those pipelines. Most data architecture today is opaque—you can’t tell what’s happening inside.

Data Pipeline 98

Data Pipeline Data Engineer Data Engineering Engineering 98

Knowledge Hut

NOVEMBER 2, 2023

An Azure Data Engineer is a professional who is in charge of designing, implementing, and maintaining data processing systems and solutions on the Microsoft Azure cloud platform. A Data Engineer is responsible for designing the entire architecture of the data flow while taking the needs of the business into account.

Data Engineer 52

Data Engineer Data Engineering Project Coding 52

Knowledge Hut

APRIL 23, 2024

It encompasses data from diverse sources such as social media, sensors, logs, and multimedia content. The key characteristics of big data are commonly described as the three V's: volume (large datasets), velocity (high-speed data ingestion), and variety (data in different formats).

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Ascend.io

JANUARY 2, 2024

The sources of data can be incredibly diverse, ranging from data warehouses, relational databases, and web analytics to CRM platforms, social media tools, and IoT device sensors. Regardless of the source, data ingestion, which usually occurs in batches or as streams, is the critical first step in any data pipeline.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

Data Engineering Weekly

NOVEMBER 13, 2022

link] Meta: Tulip - Schematizing Meta’s data platform Numerous heterogeneous services make up a data platform, such as warehouse data storage and various real-time systems. The schematization of data plays a vital role in a data platform. The author shares the experience of one such transition.

Data Engineer 52

Data Engineer Data Engineering Engineering Kafka 52

Knowledge Hut

OCTOBER 3, 2023

The task of integrating, manipulating, and merging data from diverse structured and unstructured sources into a structure utilized to build analytics solutions falls within the purview of an Azure Data Engineer, a highly qualified specialist. As a result, they can work on a number of projects and use cases.

Data Engineer 52

Data Engineer Data Engineering Engineering Cloud Computing 52

AltexSoft

SEPTEMBER 21, 2023

These diverse use cases demonstrate the engine’s versatility, making it a popular choice for organizations dealing with various data types and requiring fast, actionable insights. Key components of the Elasticsearch architecture. Each document is a collection of fields, the basic data units to be searched.

Engineering 52

Engineering NoSQL Programming Language Java 52

Monte Carlo

JUNE 2, 2024

A venn diagram comparing common responsibilities of data infrastructure engineers and data science engineers. For example, Data Infrastructure Engineers use their programming skills to lead system architecture and data engineering efforts. Engineers should make sure to monitor these pipelines as well.

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

Monte Carlo

JUNE 2, 2024

A venn diagram comparing common responsibilities of data infrastructure engineers and data science engineers. For example, Data Infrastructure Engineers use their programming skills to lead system architecture and data engineering efforts. Engineers should make sure to monitor these pipelines as well.

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

Snowflake

JUNE 5, 2024

Comparison of Snowflake Copilot and Cortex Analyst Cortex Search: Deliver efficient and accurate enterprise-grade document search and chatbots Cortex Search is a fully managed search solution that offers a rich set of capabilities to index and query unstructured data and documents. Our state-of-the-art hybrid search enables better results.

Coding 91

Coding Building Management Government 91

Knowledge Hut

MARCH 20, 2024

An Azure Data Engineer is a professional specializing in designing, implementing, and managing data solutions on the Microsoft Azure cloud platform. They possess expertise in various aspects of data engineering. As an Azure data engineer myself, I was responsible for managing data storage, processing, and analytics.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Governance 52

Knowledge Hut

MARCH 15, 2024

An Azure Data Engineer is a professional specializing in designing, implementing, and managing data solutions on the Microsoft Azure cloud platform. They possess expertise in various aspects of data engineering. As an Azure data engineer myself, I was responsible for managing data storage, processing, and analytics.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Governance 52

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Edureka

JULY 16, 2024

Machine Learning in AWS SageMaker Machine learning in AWS SageMaker involves steps facilitated by various tools and services within the platform: Data Preparation: SageMaker comprises tools for labeling the data and data and feature transformation.

AWS 52

AWS Algorithm Machine Learning Amazon Web Services 52

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Find sources of relevant data. Choose data collection methods and tools.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

JANUARY 18, 2024

Let us now look into the differences between AI and Data Science: Data Science vs Artificial Intelligence [Comparison Table] SI Parameters Data Science Artificial Intelligence 1 Basics Involves processes such as data ingestion, analysis, visualization, and communication of insights derived.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. In Snowflake, there are three different storage layers available, Database, Stage, and Cloud Storage.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52