Cloudera

DECEMBER 21, 2020

In this blog we will take you through a persona-based data adventure, with short demos attached, to show you the A-Z data worker workflow expedited and made easier through self-service, seamless integration, and cloud-native technologies. In our data adventure we assume the following: . The Data Scientist.

Data 98

Data Virtualization Banking Data Engineering 98

Mobilunity

MAY 8, 2023

Companies may store and handle data in a safe and lawful way with the assistance of data lake consulting services and financial services data lake solutions. For companies that need to store and process massive amounts of data in a flexible and affordable way, Azure Data Lake services may be helpful.

Engineering 52

Engineering Data Storage AWS 52

Cloudera

JUNE 7, 2022

Sure we can help you secure, manage, and analyze PetaBytes of structured and unstructured data. We do that on-prem with almost 1 ZB of data under management – nearly 20% of that global total. We can also do it with your preferred cloud – AWS, Azure or GCP. Let us work with you on your hybrid data journey.

Data 115

Data Architecture Analytics Government 115

Xebia

JULY 28, 2023

Introduction In a previous Blog post, I discussed how to manage multiple BigQuery projects with one dbt Cloud project. Setup the Azure Service Principal : We want to avoid Personal Tokens that are associated with a specific user as much as possible, so we will use a SP to authenticate dbt with Databricks.

Cloud 130

Cloud Azure How To Windows 130

Datavail

JUNE 8, 2023

From DBA to Data Engineer—The Strategic Role of DBAs in the Cloud Over the past few years, the IT landscape has experienced significant disruptions. Doughty also discussed how automation and cloud adoption are changing traditional DBA duties as well as providing a platform for greater efficiency and scalability.

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

Perficient

FEBRUARY 16, 2024

In the world of big data processing, efficient and scalable file systems play a crucial role. In this blog post, we’ll explore into what DBFS is, how it works, and provide examples to illustrate its usage. DBFS provides a unified interface to access data stored in various underlying storage systems. What is DBFS?

System 52

System Storage Azure Big Data 52

Perficient

APRIL 1, 2024

Traditionally, organizations used to provision multiple services of Azure Services, like Azure Storage, Azure Databricks, etc. This data needs to be ingested on a real-time basis into the warehouse, for further usage by the data scientist & data analyst team.

Data 64

Data Azure Case Study Data Engineering 64

Cloudera

DECEMBER 15, 2022

You can leverage Kubernetes (K8s) and containerization technologies to consistently deploy your applications across multiple clouds including AWS, Azure, and Google Cloud, with portability to write once, run anywhere, and move from cloud to cloud with ease. Performance and scalability. Read why the future of data lakehouses is open.

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Cloud Data Analytics Artificial Inteligence 82

Cloudera

SEPTEMBER 28, 2021

We covered the value this new capability provides in a previous blog. RAZ for S3 and RAZ for ADLS introduce FGAC and Audit on CDP’s access to files and directories in cloud storage making it consistent with the rest of the SDX data entities. Let’s say that both Jon and Remi belong to the Data Engineering group.

Groups 64

Groups Cloud AWS Data 64

OpenCredo

FEBRUARY 6, 2024

This use case was chosen because it involves semi-structured documents with quite a high density of information, rather than free flowing and verbose texts such as this blog post, so could present more of a challenge for the application. The two main services we will be using are AWS Bedrock and Azure OpenAI.

Artificial Inteligence 59

Artificial Inteligence Knowledge Base AWS Azure 59

Palo Alto Networks

AUGUST 23, 2021

we are leveraging ML-based threat detectors against an extensive set of identity data sources, including Active Directory, Identity and Access Management products (including Okta, Ping and Azure AD), human resources (HR) platforms (like Workday) and SASE gateways. appeared first on Palo Alto Networks Blog. With Cortex XDR 3.0,

Cloud 92

Cloud Artificial Inteligence Machine Learning Analytics 92

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. What is Apache Airflow?

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Weak Development Team Technical Review Software Review Systems Review 52

Cloudera

SEPTEMBER 9, 2018

It enables organizations to address their data warehousing reporting needs by making it quick and easy to consolidate data into a single repository yet still service your users’ needs in a scalable and cost-effective way. This makes it easy to meet the ever-changing needs of your data teams.

Data 40

Data Data Engineering Analytics Cloud 40

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. Still, it’s the number one choice for data-driven companies, and here’re some reasons why. Scalability.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Cloudera

OCTOBER 26, 2017

Business intelligence (BI) and analytics in the cloud is an area that has gained the attention of many organizations looking to provide a better user experience for their data analysts and engineers. The reason frequently cited for the consideration of BI in the cloud is that it provides flexibility and scalability.

Cloud 43

Cloud Data Storage Analytics 43

Cloudera

FEBRUARY 14, 2022

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. Each unlocking value in the data engineering workflows enterprises can start taking advantage of. Usage Patterns.

Data Engineering 116

Data Engineering Engineering Data Storage 116

Cloudera

MAY 18, 2021

Infrastructure cost optimization by enabling container-based scalability for compute resources based on processing load and by leveraging object storage that has lower price point than compute-attached storage. Experience configuration / use case deployment: At the data lifecycle experience level (e.g., 1 Year Reserved . 13,000-18,500.

Cloud 86

Cloud Technical Review Storage Backup 86

Cloudera

FEBRUARY 22, 2021

As a result, it is important for an enterprise data platform to enable users to minimize infrastructure costs by providing optionality in terms of both hosting type (public cloud, on-prem or hybrid) and hosting vendor (e.g., AWS, Google or Azure) and thus allow for execution of a use case wherever it is most costs effective to do so.

Data 83

Data Analytics Government Technical Review 83