AWS Machine Learning - AI

MARCH 13, 2025

The customer interaction transcripts are stored in an Amazon Simple Storage Service (Amazon S3) bucket. Its serverless architecture allowed the team to rapidly prototype and refine their application without the burden of managing complex hardware infrastructure.

Generative AI 98

Generative AI CTO Coach AWS Artificial Inteligence 98

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Supports Disaggregation of compute and storage.

Data 101

Data Storage Architecture Big Data 101

Erik Bernhardsson

DECEMBER 6, 2022

Data teams often need to change infrastructure a lot more often (sometimes every new cron job needs a Terraform update), have very “bursty” needs for compute power, and needs a much wider range of hardware (GPUs! There's a weird sort of backend-normative view of what data teams should do, but I think it's very misguided.

CTO Coach 242

CTO Coach Fractional CTO Software Engineering Serverless 242

CIO

JUNE 19, 2024

Bring the right skills onboard As a baseline, every platform engineering team needs to hire people who have strong communication skills, are technically proficient in software development, hardware and data, have excellent analytical and problem solving skills, and are familiar with platform engineering tools, says Atkinson.

Weak Development Team 208

Weak Development Team Engineering UI/UX Software Development 208

Cloudera

AUGUST 26, 2020

Informatica and Cloudera deliver a proven set of solutions for rapidly curating data into trusted information. Informatica’s comprehensive suite of Data Engineering solutions is designed to run natively on Cloudera Data Platform — taking full advantage of the scalable computing platform.

Data 84

Data Artificial Inteligence Machine Learning Disaster Recovery 84

Altexsoft

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. Is it still so? Scalability opportunities.

Backup 115

Backup Azure Software Review Architecture 115

Cloudera

SEPTEMBER 29, 2020

CDW outperformed HDInsight by over 40% in total query runtime for TPC-DS queries using the same hardware specs (see Figure 1). A TPC-DS 10TB dataset was generated in ACID ORC format and stored on the ADLS Gen 2 cloud storage. Cloudera Data Warehouse vs HDInsight. Queries on CDW run on an average 2.7x

Azure 120

Azure Data Comparison Virtualization 120

CIO

JUNE 14, 2023

Going from petabytes (PB) to exabytes (EB) of data is no small feat, requiring significant investments in hardware, software, and human resources. Start with storage. Before you can even think about analyzing exabytes worth of data, ensure you have the infrastructure to store more than 1000 petabytes! Much larger.

Data 97

Data Scalability Storage Big Data 97

Altexsoft

MARCH 31, 2020

It means you must collect transactional data and move it from the database that supports transactions to another system that can handle large volumes of data. And, as is common, to transform it before loading to another storage system. But how do you move data? You need an efficient data pipeline. Destination.

Data 76

Data Storage Analytics Data Center 76

Kentik

APRIL 4, 2023

However, arriving at specs for other aspects of network performance requires extensive monitoring, dashboarding, and data engineering to unify this data and help make it meaningful. No matter how you slice it, additional instances, hardware, etc., Costs Redundancy isn’t cheap. will simply cost more than having fewer.

Network 104

Network Load Balancer Cloud Backup 104

Altexsoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. What is the main difference between a data architect and a data engineer? By the way, we have a video dedicated to the data engineering working principles.

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

NOVEMBER 28, 2023

Cloudera Private Cloud Data Services is a comprehensive platform that empowers organizations to deliver trusted enterprise data at scale in order to deliver fast, actionable insights and trusted AI. This means you can expect simpler data management and drastically improved productivity for your business users.

Data 84

Data Scalability Analytics Quality Assurance 84

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. Stream processing.

Analytics 20

Analytics Data IoT Analysis 20

Altexsoft

JUNE 7, 2021

Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. Virtually, Hadoop puts no limits on the storage capacity. What is Hadoop.

Big Data 98

Big Data Tools Data Storage 98

Cloudera

MAY 17, 2021

CDW – Lower minimum hardware requirements. Yet for organizations that only want to get their toes wet and perhaps just evaluate the capability, the 16 cores, 128 GB RAM, and 600 GB of storage prevented them from doing just that. With Private Cloud 1.2, CML – Applied ML Prototypes. Beyond PVC 1.2. With CDP Private Cloud 1.2

Cloud 90

Cloud Artificial Inteligence Machine Learning Storage 90

Altexsoft

MARCH 18, 2021

This includes Apache Hadoop , an open-source software that was initially created to continuously ingest data from different sources, no matter its type. Cloud data warehouses such as Snowflake, Redshift, and BigQuery also support ELT, as they separate storage and compute resources and are highly scalable.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Altexsoft

OCTOBER 24, 2019

Similar to humans companies generate and collect tons of data about the past. And this data can be used to support decision making. While our brain is both the processor and the storage, companies need multiple tools to work with data. And one of the most important ones is a data warehouse. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Storage provisioning.

Big Data 63

Big Data Data Storage Microservices 63

Cloudera

APRIL 26, 2023

At its core, CDP Private Cloud Data Services (“the platform”) is an end-to-end cloud native platform that provides a private open data lakehouse. It offers features such as data ingestion, storage, ETL, BI and analytics, observability, and AI model development and deployment.

Cloud 64

Cloud Data Load Balancer Storage 64

TIBCO - Connected Intelligence

AUGUST 10, 2020

Taking action to leverage your data is a multi-step journey, outlined below: First, you have to recognize that sticking to the status quo is not an option. Your data demands, like your data itself, are outpacing your data engineering methods and teams.

Virtualization 69

Virtualization Data How To Data Engineering 69

Cloudera

NOVEMBER 2, 2020

Having a live view of all aspects of their network lets them identify potentially faulty hardware in real time so they can avoid impact to customer call/data service. Ingest 100s of TB of network event data per day . It has the key elements of fast ingest, fast storage, and immediate querying for BI purposes.

Data 97

Data Analytics Storage Big Data 97

Abhishek Tiwari

DECEMBER 27, 2017

More importantly, UDM utilizes a single storage backend with benefits of multiple storage systems which avoids moving data across systems hence data duplication, and data consistency issues. Common in-memory data interfaces. It generally improves performance by placing frequently accessed data in memory.

Trends 49

Trends Artificial Inteligence Data Big Data 49

Altexsoft

DECEMBER 9, 2020

Sometimes, a data or business analyst is employed to interpret available data, or a part-time data engineer is involved to manage the data architecture and customize the purchased software. At this stage, data is siloed, not accessible for most employees, and decisions are mostly not data-driven.

Analytics 102

Analytics Technical Review Technology Applications 102

Mentormate

OCTOBER 31, 2023

In our healthcare example, a multidisciplinary team might be necessary, encompassing data scientists and medical professionals for domain expertise and bioinformaticians for data engineering. It’s vital to anticipate both the upfront costs, like model training, and ongoing expenses, like data storage or additional software.

Artificial Inteligence 98

Artificial Inteligence Healthcare Budget Training 98

Altexsoft

APRIL 26, 2022

Not long ago setting up a data warehouse — a central information repository enabling business intelligence and analytics — meant purchasing expensive, purpose-built hardware appliances and running a local data center. By the type of deployment, data warehouses can be categorized into. Each node has its own disk storage.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. Big Data analytics processes and tools. Data ingestion.

Big Data 78

Big Data Analytics Tools Applications 78

Cloudera

FEBRUARY 1, 2024

Moreover, it is a period of dynamic adaptation, where documentation and operational protocols will adapt as your data and technology landscape change. Resource allocation: determine the hardware and cloud resources required for the installation. Network setup: configure the network infrastructure to ensure connectivity and data flow.

Backup 82

Backup Cloud Architecture Resources 82

Altexsoft

OCTOBER 2, 2020

Data is a valuable source that needs management. If your business generates tons of data and you’re looking for ways to organize it for storage and further use, you’re at the right place. Read the article to learn what components data management consists of and how to implement a data management strategy in your business.

Strategy 64

Strategy Database Administration Data Technical Review 64

ParkMyCloud

MAY 29, 2019

As more and more enterprises drive value from container platforms, infrastructure-as-code solutions, software-defined networking, storage, continuous integration/delivery, and AI, they need people and skills on board with ever more niche expertise and deep technological understanding.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

DECEMBER 4, 2020

Hardware and software become obsolete sooner than ever before. So data migration is an unavoidable challenge each company faces once in a while. Transferring data from one computer environment to another is a time-consuming, multi-step process involving such activities as planning, data profiling, testing, to name a few.

Software Review 69

Software Review Software Data Technical Review 69

Altexsoft

JULY 18, 2023

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general.

Weak Development Team 52

Weak Development Team Big Data Data Artificial Inteligence 52

Cloudera

APRIL 9, 2021

Legacy data warehouse solutions are often inefficient due to their scale-up architecture, attempting to serve multiple phases of the data lifecycle with a single monolithic architecture, ineffective management and performance tuning tools. . ETL jobs and staging of data often often require large amounts of resources.

Data 58

Data Software Review Technical Review Architecture 58

Coforge

AUGUST 20, 2019

In the digital communities that we live in, storage is virtually free and our garrulous species is generating and storing data like never before. Outsourcing: Some of the work related to data engineering and DevOps/SRE may be outsourced to concentrate resources towards achieving the business goals. #2

Artificial Inteligence 8

Artificial Inteligence Machine Learning Enterprise Software Review 8

Kentik

MAY 31, 2023

For many enterprises, applications represent only a portion of a much larger reliability mandate, including offices, robotics, hardware, and IoT, and the complex networking, data, and observability infrastructure required to facilitate such a mandate.

Network 52

Network Cloud Load Balancer Systems Review 52

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. Depending on the hardware characteristics, even a single broker is enough to form a cluster handling tens and hundreds of thousands of events per second. How Apache Kafka streams relate to Franz Kafka’s books.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Abhishek Tiwari

JULY 12, 2018

Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Not everyone is operating at Netflix or Spotify scale data engineering function. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines.

Data 63

Data Software Review Technical Review Microservices 63

Mobilunity

DECEMBER 27, 2024

Data Handling and Big Data Technologies Since AI systems rely heavily on data, engineers must ensure that data is clean, well-organized, and accessible. Hardware Optimization This skill is particularly critical in resource-constrained environments or applications requiring real-time processing.

Artificial Inteligence 52

Artificial Inteligence Technical Review Engineering Artificial Intelligence 52