Cloudera

SEPTEMBER 29, 2020

Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. . Cloudera Data Warehouse vs HDInsight.

Azure 120

Azure Data Comparison Virtualization 120

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. Resource Groups : . Beyond PVC 1.2.

Cloud 90

Cloud Machine Learning Artificial Inteligence Storage 90

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?

Backup 115

Backup Azure Software Review Systems Review 115

Cloudera

FEBRUARY 1, 2024

The other half of the equation requires your team’s emphasis to shift to sustained excellence in managing and optimizing your data ecosystem — better known as Day 2 operations. In this blog, we’ll cover the highlights of our recently published Day 2 Operations Guide and why it matters to enterprises.

Backup 82

Backup Architecture Cloud Resources 82

Kentik

MAY 31, 2023

Reliability is a massive burden for network operators While DevOps teams and their SREs focus on the reliability of the application environment, an enterprise’s network concerns often extend well beyond the uptime of a suite of customer-facing web and mobile apps.

Network 52

Network Cloud Load Balancer Firewall 52

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. The main idea of any data warehouse (DW) is to integrate data from multiple disjointed sources (e.g.,

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

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

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.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

MARCH 18, 2021

The primary difference resides in WHERE and WHEN data transformation and loading happens. With ETL, data is transformed in a temporary staging area before it gets to a target repository (e.g The data flow of both ETL and ELT relies on three core stages. Just like with extraction, data can be loaded either fully or partially.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

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

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. Cloud Consultants.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

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

Existek

JANUARY 11, 2022

It eliminated the need to get back to the traditional environment when teams struggled with complex and costly in-house hardware and software. . At some point, cloud computing has changed how to streamline business processes and deal with data in general. Let’s start with Azure, a Magic Quadrant Leader by Gartner in 2021.

Azure 52

Azure AWS Cloud How To 52

O'Reilly Media - Ideas

JANUARY 25, 2024

Our data shows that most topics in software architecture and design are down year-over-year. While software architecture is down 3.9% (a relatively small decline), enterprise architecture is up 8.9%. Domain-driven design is particularly useful for understanding the behavior of complex enterprise systems; it’s down, but only 2.0%.

Trends 115

Trends Technical Review Technology Artificial Inteligence 115

Altexsoft

MARCH 14, 2023

Modern data stack vs traditional data stack Traditional data stacks are typically on-premises solutions based on hardware and software infrastructure managed by the organization itself. This means that companies don’t necessarily need a large data engineering team. Data democratization.

Data 59

Data Technical Review Software Review Artificial Inteligence 59

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 Software Review 93

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

Machine Learning 8

Machine Learning Artificial Inteligence Enterprise Software Review 8

Altexsoft

NOVEMBER 5, 2021

To avoid errors that may threaten patient safety, AHIMA introduced the data quality management model which covers. Application, or the reason for data collection, Collection, or the process of data gathering, Warehousing, or systems and activities related to data storage and archiving, and. Supported data formats.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Cloudera

SEPTEMBER 17, 2020

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. CDP data lifecycle integration and SDX security and governance.

Data Engineering 104

Data Engineering Engineering Data Tools 104

Altexsoft

OCTOBER 8, 2021

This often includes such procedures as data profiling (searching for errors and inconsistencies), cleansing (removing duplicates, corrupted items, etc.), Data integration process. On the enterprise level, data integration may cover a wider array of data management tasks including. Data profiling and cleansing.

Tools 52

Tools Data Software Review Open Source 52

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 162

Data Scalability Storage Big Data 162

O'Reilly Media - Ideas

JANUARY 25, 2022

While our customers include many individual developers, contractors, and hobbyist programmers, commercial (enterprise) software developers are very heavily represented—although there are certainly areas into which we’d like more visibility, such as the crucial Asia-Pacific software development community.

Trends 109

Trends Technical Review Technology Artificial Inteligence 109

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

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

Kentik

APRIL 11, 2016

It has since gone on to become a key technology for running many web-scale services and products, and has also landed in traditional enterprise and government IT organizations for solving big data problems in finance, demographics, intelligence, and more. For more on how we make it work, see Inside the Kentik Data Engine.).

Big Data 40

Big Data Analytics Network Architecture 40

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

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. Data Generation at Scale.

Data 101

Data Storage Architecture Big Data 101

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 . Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture.

Data 97

Data Analytics Storage Big Data 97

Altexsoft

JUNE 6, 2019

GPUs provide a huge computational power, so systems that run on such hardware can efficiently analyze vast amounts of data and generate more accurate forecasting results. Building a data-driven organization. The demand forecasting model that runs on Nvidia GPUs (graphical processing units) achieved 1.7

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

Cloudera

APRIL 9, 2021

Enterprise data warehouse platform owners face a number of common challenges. In this article, we look at seven challenges, explore the impacts to platform and business owners and highlight how a modern data warehouse can address them. ETL jobs and staging of data often often require large amounts of resources.

Data 58

Data Software Review Technical Review Architecture 58

Cloudera

AUGUST 26, 2020

On August 18, we completed our Enterprise Data Cloud vision of bringing a truly hybrid cloud experience with the general availability of Cloudera Data Platform Private Cloud (CDP Private Cloud). Informatica and Cloudera deliver a proven set of solutions for rapidly curating data into trusted information.

Data 84

Data Machine Learning Artificial Inteligence Disaster Recovery 84

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. It’s no longer driven by data volumes, but containerization, separation of storage and compute, and democratization of analytics.

Data Engineering 113

Data Engineering Engineering Data Storage 113