Xebia

JULY 28, 2023

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. For this project, we will use Azure as our Cloud provider. We will call them data-platform-udev and data-platform-uprod.

Cloud 130

Cloud Azure How To Windows 130

Altexsoft

JANUARY 14, 2021

The variety of data explodes and on-premises options fail to handle it. Apart from the lack of scalability and flexibility offered by modern databases, the traditional ones are costly to implement and maintain. At the moment, cloud-based data warehouse architectures provide the most effective employment of data warehousing resources.

Backup 115

Backup Azure Software Review Architecture 115

Xebia

OCTOBER 23, 2024

Introduction This blog post will explore how Azure Data Factory (ADF) and Terraform can be leveraged to optimize data ingestion. ADF is a Microsoft Azure tool widely utilized for data ingestion and orchestration tasks. An Azure Key Vault is created to store any secrets.

Azure 130

Azure Software Review Technical Review Resources 130

Altexsoft

JUNE 29, 2021

MLEs are usually a part of a data science team which includes data engineers , data architects, data and business analysts, and data scientists. Who does what in a data science team. Machine learning engineers are relatively new to data-driven companies.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Existek

JANUARY 11, 2022

We suggest drawing a detailed comparison of Azure vs AWS to answer these questions. Azure vs AWS market share. What is Microsoft Azure used for? Azure vs AWS features. Azure vs AWS comparison: other practical aspects. Azure vs AWS comparison: other practical aspects. Azure vs AWS: which is better?

Azure 52

Azure AWS Cloud How To 52

CIO

FEBRUARY 13, 2023

Vaithylingam says the College of Southern Nevada will shut down its on-prem data center — one of the largest in Nevada — and plans to fully move all workloads and infrastructure to Microsoft Azure. We are working to transform ourselves into a data company mindset, finding newer ways to leverage data to support business growth.”

Budget 218

Budget Artificial Inteligence Technical Review VR 218

ParkMyCloud

JANUARY 17, 2020

Each of the ‘big three’ cloud providers (AWS, Azure, GCP) offer a number of cloud certification options that individuals can get to validate their cloud knowledge and skill set, while helping them advance in their careers and broaden the scope of their achievements. . Microsoft Azure Certifications.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Altexsoft

FEBRUARY 11, 2023

Data architect and other data science roles compared Data architect vs data engineer Data engineer is an IT specialist that develops, tests, and maintains data pipelines to bring together data from various sources and make it available for data scientists and other specialists.

Data 87

Data Data Engineering Big Data Architecture 87

AWS Machine Learning - AI

NOVEMBER 15, 2024

Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles. By integrating QnABot with Azure Active Directory, Principal facilitated single sign-on capabilities and role-based access controls.

Generative AI 120

Generative AI AWS Groups Artificial Inteligence 120

The Citus Data

MARCH 31, 2023

on-demand talk, Citus open source user) 6 Citus engineering talks Citus & Patroni: The Key to Scalable and Fault-Tolerant PostgreSQL , by Alexander Kukushkin who is a principal engineer at Microsoft and lead engineer for Patroni.

Azure 84

Azure Open Source Virtualization Software Engineering 84

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.

Cloud 85

Cloud Data Analytics Artificial Inteligence 85

Invid Group

AUGUST 28, 2024

AWS, Azure, and Google provide fully managed platforms, tools, training, and certifications to prototype and deploy AI solutions at scale. For instance, AWS Sagemaker, AWS Bedrock, Azure AI Search, Azure Open AI, and Google Vertex AI [3,4,5,6,7].

Technical Review 52

Technical Review Artificial Inteligence Performance Azure 52

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

Cloudera

JANUARY 15, 2021

Cloudera Data Warehouse is a highly scalable service that marries the SQL engine technologies of Apache Impala and Apache Hive with cloud-native features to deliver best-in-class price-performance for users running data warehousing workloads in the cloud. higher cost.

Performance 102

Performance Cloud Data Storage 102

Altexsoft

DECEMBER 4, 2020

Three types of data migration tools. Automation scripts can be written by data engineers or ETL developers in charge of your migration project. This makes sense when you move a relatively small amount of data and deal with simple requirements. Use cases: moving data from on-premises to cloud or between cloud environments.

Software Review 69

Software Review Software Data Technical Review 69

Perficient

APRIL 1, 2024

Traditionally, organizations used to provision multiple services of Azure Services, like Azure Storage, Azure Databricks, etc. Fabric enables integration of team of data scientist, data engineers & data analyst on a single unified platform.

Data 64

Data Azure Case Study Data Engineering 64

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. With Cortex XDR 3.0,

Cloud 98

Cloud Artificial Inteligence Machine Learning Analytics 98

Cloudera

DECEMBER 21, 2020

In our data adventure we assume the following: . There is an environment available on either Azure or AWS, using the company AWS account – note: in this blog, all examples are in AWS. Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake.

Data 98

Data Virtualization Banking Data Engineering 98

Kentik

MARCH 7, 2023

Despite what was supposed to be a robust and expansive series of ExpressRoutes with Azure, the retailer’s system kept experiencing cascading failures. The highly scalable model of today’s observability data pipelines requires robust and extensive reliability frameworks (similar to their parent networks).

Network 99

Network Cloud Data Case Study 99

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. Don’t just take our word for it, look at the stats.

Data 118

Data Architecture Analytics Big Data 118

Exadel

FEBRUARY 20, 2023

If you want to experiment with AI or go live with your solution, there are three widely known vendors: Amazon, Google, and Azure. Vertex AI leverages a combination of data engineering, data science, and ML engineering workflows with a rich set of tools for collaborative teams.

Artificial Inteligence 52

Artificial Inteligence Cloud Machine Learning Azure 52

Perficient

FEBRUARY 16, 2024

In the world of big data processing, efficient and scalable file systems play a crucial role. DBFS is a distributed file system that comes integrated with Databricks, a unified analytics platform designed to simplify big data processing and machine learning tasks. What is DBFS? How does DBFS work?

System 52

System Storage Azure Big Data 52

Mobilunity

DECEMBER 9, 2024

ML algorithms for predictions and data-based decisions; Deep Learning expertise to analyze unstructured data, such as images, audio, and text; Mathematics and statistics. Google Professional Machine Learning Engineer implies developers knowledge of design, building, and deployment of ML models using Google Cloud tools.

Artificial Inteligence 52

Artificial Inteligence Engineering Machine Learning Artificial Intelligence 52

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview.

Analytics 20

Analytics Data IoT Analysis 20

Cloudera

SEPTEMBER 28, 2021

Each policy change, or introduction of a new user or new group typically requires interaction between CDP administrators and AWS/Azure administrators and potential changes to existing applications. Let’s say that both Jon and Remi belong to the Data Engineering group. Without RAZ: Group-based access control with IDBroker.

Groups 65

Groups Cloud Data AWS 65

O'Reilly Media - Ideas

MARCH 1, 2023

Decomposing a complex monolith into a complex set of microservices is a challenging task and certainly one that can’t be underestimated: developers are trading one kind of complexity for another in the hope of achieving increased flexibility and scalability long-term. Data engineering was the dominant topic by far, growing 35% year over year.

Trends 134

Trends Technical Review Technology Software Review 134

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

Datavail

JUNE 20, 2023

Percona Live 2023 was an exciting open-source database event that brought together industry experts, database administrators, data engineers, and IT leadership. Keynotes, breakout sessions, workshops, and panel discussions kept the database conversations going throughout the event.

Open Source 52

Open Source Database Administration Survey AWS 52

Altexsoft

OCTOBER 2, 2020

Data integration and interoperability: consolidating data into a single view. Specialist responsible for the area: data architect, data engineer, ETL developer. They bring data to a single platform giving a cohesive view of the business. Cloudera Data Platform: enterprise data cloud for any data type.

Strategy 64

Strategy Database Administration Data Technical Review 64

InnovationM

MAY 14, 2023

Technologies Behind Data Lake Construction Distributed Storage Systems: When building data lakes, distributed storage systems play a critical role. These systems ensure high availability and facilitate the storage of massive data volumes. Data Ingestion Tools: The journey of constructing a data lake starts with data ingestion.

Data 52

Data Storage Construction Business Intelligence 52

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 Open Source 93

OpenCredo

FEBRUARY 6, 2024

The two main services we will be using are AWS Bedrock and Azure OpenAI. These are the two setups we will be using for the tests: Azure OpenAI RAG app: Text embedding: OpenAI’s text-embedding-ada-002 Text generation: GPT 3.5 The results from asking our test set of questions was impressive, it got them all completely correct!

Artificial Inteligence 59

Artificial Inteligence Knowledge Base AWS Azure 59

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

O'Reilly Media - Ideas

JUNE 4, 2019

Programming with Data: Advanced Python and Pandas , July 9. Understanding Data Science Algorithms in R: Regression , July 12. Cleaning Data at Scale , July 15. Scalable Data Science with Apache Hadoop and Spark , July 16. Effective Data Center Design Techniques: Data Center Topologies and Control Planes , July 19.

Course 68

Course Training Artificial Inteligence Software Review 68

Altexsoft

JULY 29, 2022

What happens, when a data scientist, BI developer , or data engineer feeds a huge file to Hadoop? Under the hood, the framework divides a chunk of Big Data into smaller, digestible parts and allocates them across multiple commodity machines to be processed in parallel. Scalability. Apache Hadoop architecture.

Big Data 59

Big Data Data Google Cloud Open Source 59

Altexsoft

APRIL 26, 2022

With the consistent rise in data volume, variety, and velocity, organizations started seeking special solutions to store and process the information tsunami. This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance. Modern data pipeline with Snowflake technology as its part.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Scalability. Please note!

Tools 52

Tools Software Review Systems Review Testing 52