CIO

JUNE 19, 2024

They may also ensure consistency in terms of processes, architecture, security, and technical governance. Our platform engineering teams, which support more than 200 applications, have innovated around automation,” says Bob Simms, former director of enterprise infrastructure delivery at the US Patent and Trademark Office (USPTO).

Weak Development Team 208

Weak Development Team Engineering UI/UX Software Development 208

Cloudera

OCTOBER 13, 2020

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data. Predict – Data Engineering (Apache Spark).

Cloud 97

Cloud Machine Learning Artificial Inteligence Data Engineering 97

Cloudera

OCTOBER 29, 2020

From our release of advanced production machine learning features in Cloudera Machine Learning, to releasing CDP Data Engineering for accelerating data pipeline curation and automation; our mission has been to constantly innovate at the leading edge of enterprise data and analytics. Data sources across the lifecycle.

Data 111

Data Machine Learning Artificial Inteligence Analytics 111

Palo Alto Networks

AUGUST 23, 2021

the third-generation XDR platform that allows security teams to identify and investigate attacks across all endpoint, network, cloud and identity sources from a single console. taking a significant step in our mission to know about and stop all cybersecurity attacks. Announcing Cortex XDR 3.0, Today, we released Cortex XDR 3.0,

Cloud 98

Cloud Artificial Inteligence Machine Learning Analytics 98

Cloudera

OCTOBER 7, 2021

Comprehensive Data Security: Access to data assets should be governed by a robust security mechanism that ensures authentication for data participants based on enterprise-wide standards (data participants being data producers and consumers) and applies fine-grained data access permissions based on the data types (e.g.,

Architecture 124

Architecture Data Security Technical Review 124

Abhishek Tiwari

FEBRUARY 26, 2020

There are no hard-and-fast rules to figure out interdependency between technology architecture and engineering organization but below is what I think can really work well for product startup. Secure you APIs via standard based authentication (JWT tokens). Introduce site-reliability engineering best-practices (SLI/SLOs).

Architecture 82

Architecture MVC Engineering Organization 82

Cloudera

FEBRUARY 22, 2021

Providing a comprehensive set of diverse analytical frameworks for different use cases across the data lifecycle (data streaming, data engineering, data warehousing, operational database and machine learning) while at the same time seamlessly integrating data content via the Shared Data Experience (SDX), a layer that separates compute and storage.

Data 82

Data Analytics Government Technical Review 82

Cloudera

NOVEMBER 1, 2022

These systems also pose security risks, including the inability to use current security best practices, such as data encryption and multi-factor authentication, making these systems particularly vulnerable to malicious cyber activity. Data is one of the DoD’s most strategic assets.

Cloud 89

Cloud Government Analytics Storage 89

Netflix Tech

JUNE 6, 2022

By Astha Singhal , Lakshmi Sudheer , Julia Knecht The Application Security teams at Netflix are responsible for securing the software footprint that we create to run the Netflix product, the Netflix studio, and the business. Our customers are product and engineering teams at Netflix that build these software services and platforms.

Software Review 70

Software Review Software Engineering Scalability Engineering 70

AWS Machine Learning - AI

AUGUST 14, 2024

Amazon Q Business is a fully managed generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. Refer to ServiceNow data source connector field mappings documentation for more information.

Generative AI 119

Generative AI Artificial Inteligence AWS Technical Review 119

The Citus Data

MARCH 31, 2023

(on-demand talk, Citus open source user, Django, Python, django-multitenant, pgBackRest) Practical approach to building real-time analytics for cybersecurity applications , by Slava Moudry. (on-demand on-demand talk, security, roles, privileges, PostgreSQL) How to copy a Postgres database? ,

Azure 84

Azure Open Source Virtualization Software Engineering 84

Cloudera

AUGUST 20, 2021

The Cloudera Data Platform comprises a number of ‘data experiences’ each delivering a distinct analytical capability using one or more purposely-built Apache open source projects such as Apache Spark for Data Engineering and Apache HBase for Operational Database workloads. A Robust Security Framework.

Strategy 98

Strategy Data Technical Review Weak Development Team 98

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. Now that we have our Databricks Workspace and SQL Warehouse instance configured, it is time to start dealing with authentication.

Cloud 130

Cloud Azure How To Windows 130

Cloudera

OCTOBER 25, 2022

“They combine the best of both worlds: flexibility, cost effectiveness of data lakes and performance, and reliability of data warehouses.”. It allows users to rapidly ingest data and run self-service analytics and machine learning. Security function isolation. Cloud platform hardening.

Cloud 52

Cloud Data Firewall AWS 52

Cloudera

DECEMBER 15, 2022

With a common interface in CDP that works across different cloud service providers, you can break down data silos while ensuring consistent security, governance, and traceability, all while seamlessly moving your Apache Iceberg – based workloads across deployment environments frictionlessly. Advanced capabilitie.

Cloud 80

Cloud Data Analytics Artificial Inteligence 80

Cloudera

JULY 24, 2023

That first step requires integrating the latest versions of all required open source projects, including not just data processing engines (e.g., Apache Zookeeper), and security / governance (Apache Ranger and Apache Atlas). That process is a complicated development workflow that requires substantial engineering effort.

Open Source 66

Open Source Analytics Software Review Metrics 66

Cloudera

DECEMBER 14, 2020

Today, a new modern data platform is here to transform how businesses take advantage of real-time analytics. Cloudera Data Platform (CDP) is the new data cloud built for the enterprise. Apache Kafka helps data administrators and streaming app developers to buffer high volumes of streaming data for high scalability.

Analytics 71

Analytics Big Data Government Cloud 71

Altexsoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

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. Phases of the data migration process. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

Kentik

JULY 24, 2017

Five Reasons the Kentik Detect SaaS is Secure. Data is available for querying in under three seconds from receipt. In fact, depending on the type of organization, we often hear concern from the network operations team about whether the security team will let them export NetFlow to the cloud. SaaS as a Safe Solution.

Cloud 40

Cloud Big Data Data Engineering Internet 40

DataRobot

MARCH 16, 2023

To work effectively, data scientists need agility in the form of access to enterprise data, streamlined tooling, and infrastructure that just works. Agility and enterprise security, compliance, and governance are often at odds. The prototyping loop, particularly the ML data prep for each new experiment, is tedious at best.

Data 52

Data Machine Learning Artificial Inteligence Agile 52

Progress

DECEMBER 30, 2019

AWS Amplify is a good choice as a development platform when: Your team is proficient with building applications on AWS with DevOps, Cloud Services and Data Engineers. You’re developing a greenfield application that doesn’t require any external data or auth systems. You have existing backend services developed on AWS.

AWS 52

AWS DevOps Disaster Recovery Serverless 52

Progress

DECEMBER 30, 2019

AWS Amplify is a good choice as a development platform when: Your team is proficient with building applications on AWS with DevOps, Cloud Services and Data Engineers. You’re developing a greenfield application that doesn’t require any external data or auth systems. You have existing backend services developed on AWS.

AWS 52

AWS DevOps Disaster Recovery Serverless 52

Progress

DECEMBER 30, 2019

AWS Amplify is a good choice as a development platform when: Your team is proficient with building applications on AWS with DevOps, Cloud Services and Data Engineers. You’re developing a greenfield application that doesn’t require any external data or auth systems. You have existing backend services developed on AWS.

AWS 10

AWS DevOps Disaster Recovery Serverless 10

Openxcell

MAY 8, 2023

Why Is Data Leakage Prevention Important? Data leakage detection is essential to avoid long-term & short-term consequences. If you’re still in doubt about how to prevent data leakage, hire a big data engineer. What’s the Difference Between a Data Leak and a Data Breach?

Data 52

Data Software Review Technical Review Systems Review 52

Altexsoft

NOVEMBER 5, 2021

Health information management (HIM) is a set of practices to organize medical data so that it can be effectively used for enhancing the quality of care. It aims at making the right health content accessible whenever it’s required, at the same time ensuring its high quality and security. Security management.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Trigent

JANUARY 18, 2023

Technologies such as serverless cloud technology, Product, Quality, and Data engineering, to name a few, have minimized development costs and improved productivity and scalability with ease of customization. The recognition stands as a support to developing trust and authenticity within the B2B community.

Software Review 52

Software Review Technical Review Systems Review Software 52

InnovationM

MAY 14, 2023

These tools connect directly to the data lake, allowing users to gain actionable insights and communicate findings effectively. Data Security and Privacy: Data security is paramount in data lakes, as they house valuable and sensitive information.

Data 52

Data Storage Construction Business Intelligence 52

AWS Machine Learning - AI

SEPTEMBER 3, 2024

This solution enables you to process massive volumes of textual data, generate relevant embeddings , and store them in a powerful vector database for seamless retrieval and generation. Authentication mechanism When integrating EMR Serverless in SageMaker Studio, you can use runtime roles.

Serverless 117

Serverless AWS Artificial Inteligence Big Data 117

InnovationM

FEBRUARY 1, 2024

401 Unauthorized: This status code indicates that the client needs to authenticate itself to access the requested resource. c) Security Related Test Cases: Authentication and Authorization : Authentication is the process of verifying who a user is, while authorization is the process of verifying what they can access.

Testing 52

Testing Software Review Authentication Resources 52

Netflix Tech

SEPTEMBER 10, 2024

Once they receive the voice command, we allow them to make an authenticated call through apiproxy , our streaming edge proxy, to our internal voice service. This call includes metadata, such as the user’s information and details about the command, such as the specific show to play.

Systems Review 93

Systems Review Software Review Technical Review Policies 93

Cloudera

NOVEMBER 13, 2017

The net result is much improved productivity for data engineers, data scientists, and analysts. Unified – Conceptually, cloud sounds like a single place to host diverse, data-intensive functions. End-user focused tools accelerate daily tasks like job submission, performance tuning, and workload analytics.

Analytics 40

Analytics Cloud Big Data Machine Learning 40

Cloudera

SEPTEMBER 1, 2020

Provides perimeter security. It intercepts REST/HTTP calls and provides authentication, authorization, audit, URL rewriting, web vulnerability removal and other security services through a series of extensible interceptor pipelines. Knox is a stateless reverse proxy framework.

Data 71

Data Backup Disaster Recovery Storage 71

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. All data goes through the middleman — in our case, Kafka — that manages messages and ensures their security. So, if your topic contains sensitive information, it can’t be pulled by an unauthorized consumer.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

TIBCO - Connected Intelligence

JANUARY 8, 2021

Read this whitepaper by Mike Ferguson of Intelligent Business Strategies on how to accelerate your cloud migration with data virtualization. Keep Your Data Secure Data virtualization’s authentication and authorization security functions protect your data from improper use before, during, and after migration.

Virtualization 38

Virtualization Data Analytics Infrastructure 38

Altexsoft

APRIL 26, 2022

With Snowflake, multiple data workloads can scale independently from one another, serving well for data warehousing, data lakes , data science, data sharing, and data engineering. BTW, we have an engaging video explaining how data engineering works. Adequate security and data protection.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Kentik

SEPTEMBER 11, 2015

FDW backends can be a surprisingly powerful tool when your data model isn’t classically relational but you still want all the nice things that come with PostgreSQL (aggregates, client libraries, authentication, group by, etc.). Once things are installed, create a new table by installing the FWD extension (actually a.so

Data 40

Data Authentication Data Engineering Scalability 40