Altexsoft

AUGUST 25, 2020

Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data. Prominent enterprises in numerous sectors including sales, marketing, research, and healthcare are actively collecting big data. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

Apiumhub

AUGUST 12, 2021

His current technical expertise focuses on integration platform implementations, Azure DevOps, and Cloud Solution Architectures. Laurent Picard – Developer Advocate @Google Laurent is a developer passionate about software, hardware, science, and everything shaping the future. Twitter: [link] Linkedin: [link]. Twitter: ??

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Altexsoft

OCTOBER 24, 2019

In this article, we will discuss what an enterprise data warehouse is, its types and functions, and how it’s used in data processing. We will define how enterprise warehouses are different from the usual ones, what types of data warehouses exist, and how they work. What is an Enterprise Data Warehouse?

Architecture 50

Architecture Enterprise Data Technical Review 50

Cloudera

DECEMBER 20, 2023

Cloudera is launching and expanding partnerships to create a new enterprise artificial intelligence “AI” ecosystem. That’s why we’re building an ecosystem of technology providers to make it easier, more economical, and safer for our customers to maximize the value they get from AI. We’ll start with the enterprise AI stack.

Artificial Inteligence 71

Artificial Inteligence Artificial Intelligence Enterprise Machine Learning 71

Altexsoft

JUNE 11, 2021

Now, scale it to the enterprise level and just imagine how many processes comprise the daily workflow — and how many optimization opportunities there are IF you could break down and analyze every step of every process. The biggest challenge here is the increased complexity of data architecture.

Applications 69

Applications Weak Development Team Systems Review Software Review 69

Kentik

APRIL 11, 2016

Clustered computing for real-time Big Data analytics. The concept of parallel processing based on a “clustered” multi-computer architecture has a long history dating back at least as far as Gene Amdahl’s work at IBM in the 1960s. For more on how we make it work, see Inside the Kentik Data Engine.).

Big Data 40

Big Data Analytics Network Architecture 40

Cloudera

NOVEMBER 12, 2020

Traditional on-premise architectures, which create a fixed, finite set of resources, forces every business request for new insight to be a crazy resource balancing act, coupled with long wait times, or a straight-up no, it cannot be done. A tale of two organizations. We see it everywhere.

Data Center 102

Data Center Cloud Data Policies 102

Cloudera

APRIL 26, 2023

Can you achieve similar outcomes with your on-premises data platform? Application modernization initiatives have led to cloud native architectures gaining popularity on premises, making it a sensible choice to extend to your data platform. This is exactly where cloud native architectures excel, and why they are so popular.

Cloud 64

Cloud Data Load Balancer Storage 64

O'Reilly Media - Ideas

MARCH 18, 2020

The update sheds light on what AI adoption looks like in the enterprise— hint: deployments are shifting from prototype to production—the popularity of specific techniques and tools, the challenges experienced by adopters, and so on. Data scientists dominate, but executives are amply represented. Industry of survey respondents.

Enterprise 131

Enterprise Survey Technical Review Weak Development Team 131

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

O'Reilly Media - Ideas

JANUARY 25, 2024

While we like to talk about how fast technology moves, internet time, and all that, in reality the last major new idea in software architecture was microservices, which dates to roughly 2015. Who wants to learn about design patterns or software architecture when some AI application may eventually do your high-level design?

Trends 116

Trends Technical Review Technology Artificial Inteligence 116

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 81

Data Scalability Analytics Quality Assurance 81

Cloudera

JUNE 14, 2021

How to optimize an enterprise data architecture with private cloud and multiple public cloud options? Enterprise end-customers too are looking to service providers to provide SLAs and contracted assurances of availability and uptime, which is adding to the pressure. The Surging Importance of Data.

Telecommunications 94

Telecommunications Cloud Data Virtualization 94

Altexsoft

JANUARY 14, 2021

We’ll review all the important aspects of their architecture, deployment, and performance so you can make an informed decision. Before jumping into the comparison of available products right away, it will be a good idea to get acquainted with the data warehousing basics first. A data warehouse is often abbreviated as DW or DWH.

Backup 115

Backup Azure Software Review Systems Review 115

O'Reilly Media - Ideas

FEBRUARY 11, 2020

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. An additional 7% are data engineers.

Weak Development Team 127

Weak Development Team Data Technical Review Survey 127

Altexsoft

MARCH 31, 2020

Only after these actions can you analyze data with dedicated software (a so-called online analytical processing or OLAP system). But how do you move data? You need to have infrastructure, hardware and/or software, that will allow you to do that. You need an efficient data pipeline. What is a data pipeline?

Data 76

Data Storage Analytics Data Center 76

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. Standard Benchmarks.

Data 99

Data Storage Architecture Big Data 99

Altexsoft

FEBRUARY 8, 2021

Machine learning techniques analyze big data from various sources, identify hidden patterns and unobvious relationships between variables, and create complex models that can be retrained to automatically adapt to changing conditions. Data can be obtained from both inside your organization across different departments and outside it.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

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. Data warehousing in a nutshell. CRMs, OLAP/OLTP databases, enterprise applications, etc.)

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

O'Reilly Media - Ideas

MARCH 1, 2023

Content about software development was the most widely used (31% of all usage in 2022), which includes software architecture and programming languages. Software development is followed by IT operations (18%), which includes cloud, and by data (17%), which includes machine learning and artificial intelligence. growth over 2021.

Trends 134

Trends Technical Review Technology Software Review 134

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 93

Data Analytics Storage Big Data 93

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

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. Visual search engines use artificial neural networks (ANN) – computing systems which architecture was inspired by the way human brains work.

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

Altexsoft

OCTOBER 2, 2020

Key disciplines and roles in data management. Data architecture: aligning technologies with business goals. Specialist responsible for the area: data architect. Data architecture is a starting point for any data management model. Data modeling: creating useful and meaningful data entities.

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 These are data engineers who are responsible for implementing these processes. You deal with cloud projects or hybrid architectures.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. The number of possible applications tends to grow due to the rise of IoT , Big Data analytics , streaming media, smart manufacturing, predictive maintenance , and other data-intensive technologies.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

TIBCO - Connected Intelligence

AUGUST 10, 2020

Your data demands, like your data itself, are outpacing your data engineering methods and teams. You’ll discover that they all have identified data virtualization as a must-have addition to your data integration tooling and a critical enabler to a more modern, distributed data architecture.

Virtualization 69

Virtualization Data How To Data Engineering 69

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. Snaplogic iPaaS architecture.

Tools 52

Tools Data Software Review Open Source 52

Altexsoft

SEPTEMBER 28, 2021

This compact, low-level language runs on a Python virtual machine (PVM), which is software that mimics the work of the real hardware. By contrast, a low-level language offers little to no human-readable elements, as it sits close to hardware and is often optimized for a specific CPU (central processing unit.). Dynamic semantics.

Weak Development Team 94

Weak Development Team Programming Software Review Systems Review 94

Altexsoft

NOVEMBER 5, 2021

A more advanced version is the enterprise Master Patient Index (eMPI) that brings together patient documents stored in multiple sources and thus facilitates cross-system information sharing. Patient identity management with Enterprise Master Patient Index. If so, the MPI assigns them the same enterprise identifier.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

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. And, with exponentially increasing computing power and newer chip architectures, Machine Learning (ML) has emerged as a powerful technique for building models over Big Data to predict outcomes.

Machine Learning 8

Machine Learning Artificial Inteligence Enterprise Software Review 8

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

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 81

Data Machine Learning Artificial Inteligence Disaster Recovery 81

Cloudera

MAY 3, 2021

Cloudera sees success in terms of two very simple outputs or results – building enterprise agility and enterprise scalability. In the last five years, there has been a meaningful investment in both Edge hardware compute power and software analytical capabilities. Democratization of Data. A rare breed.

Scalability 101

Scalability Agile Data Systems Review 101

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. Auto scaling workloads on the fly leading to better hardware utilization. For part 1 please go here. Usage Patterns.

Data Engineering 112

Data Engineering Engineering Data Storage 112

O'Reilly Media - Ideas

JANUARY 25, 2022

What are the bigger changes shaping the future of software development and software architecture? A quick look at bigram usage (word pairs) doesn’t really distinguish between “data science,” “data engineering,” “data analysis,” and other terms; the most common word pair with “data” is “data governance,” followed by “data science.”

Trends 109

Trends Technical Review Technology Artificial Inteligence 109

Hu's Place - HitachiVantara

JANUARY 15, 2019

For lack of similar capabilities, some of our competitors began implying that we would no longer be focused on the innovative data infrastructure, storage and compute solutions that were the hallmark of Hitachi Data Systems.

Systems Review 72

Systems Review Storage System Software Review 72