Altexsoft

DECEMBER 9, 2020

In the era of global digital transformation , the role of data analysis in decision-making increases greatly. Still, today, according to Deloitte research, insight-driven companies are fewer than those not using an analytical approach to decision-making, even though the majority agrees on its importance. Stages of analytics maturity.

Analytics 102

Analytics Technical Review Technology Applications 102

Netflix Tech

OCTOBER 28, 2021

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.

Data Engineering 69

Data Engineering Engineering Data Software Engineering 69

Altexsoft

JUNE 25, 2019

Being at the top of data science capabilities, machine learning and artificial intelligence are buzzing technologies many organizations are eager to adopt. However, they often forget about the fundamental work – data literacy, collection, and infrastructure – that must be done prior to building intelligent data products.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Trigent

JUNE 20, 2022

To do this, they are constantly looking to partner with experts who can guide them on what to do with that data. This is where data engineering services providers come into play. Data engineering consulting is an inclusive term that encompasses multiple processes and business functions.

Data Engineering 52

Data Engineering Engineering Data Strategy 52

Altexsoft

APRIL 22, 2020

But, understanding and interpreting data is just a final stage in a long way, as the information goes from its raw format to the fancy analytical boards. So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

CIO

SEPTEMBER 2, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

AUGUST 31, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

Altexsoft

APRIL 16, 2021

Later, this data can be: modified to maintain the relevance of what was stored, used by business applications to perform its functions, for example check product availability, etc. used for analytical purposes to understand how our business is running. So, we need a solution that’s capable of representing data from multiple dimensions.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

CIO

FEBRUARY 13, 2023

The economy may be looking uncertain, but technology continues to drive the business and CIOs are investing big in 2023. At the same time, they are defunding technologies that no longer contribute to business strategy or growth. This technology will help our customers get started quicker and will also allow us to reach more people.”

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. This greatly increases data processing capabilities.

Big Data 75

Big Data Data Engineering Engineering Data 75

Mobilunity

AUGUST 3, 2021

While Big Data has come far, its use is still growing and being explored. Technologies that have expanded Big Data possibilities even further are cloud computing and graph databases. Who is Big Data Engineer? Big Data requires a unique engineering approach. Big Data Engineer vs Data Scientist.

Big Data 52

Big Data Data Engineering Engineering Data 52

Cloudera

DECEMBER 20, 2022

In this respect, several studies project that a proper use of advanced analytics implies savings of between 5% and 7.5%. McKinsey estimates that the use of data-driven technologies can drive operating and maintenance cost savings of more than 12%.

Energy 79

Energy Analytics Data Machine Learning 79

The Crazy Programmer

NOVEMBER 6, 2021

IT or Information technology is the industry that has registered continuous growth. The Indian information Technology has attained about $194B in 2021 and has a 7% share in GDP growth. Because startups like Zerodha, Ola, and Rupay to large organizations like Infosys, HCL Technologies Ltd, all will grow at a mass scale.

Artificial Inteligence 290

Artificial Inteligence Artificial Intelligence Blockchain Software Review 290

CIO

FEBRUARY 14, 2023

DataStax Real-time data and decisioning First, a few quick definitions. Real-time data involves a continuous flow of data in motion. It’s streaming data that’s collected, processed, and analyzed on a continuous basis. report they have established a data culture 26.5% report they have a data-driven organization 39.7%

Artificial Inteligence 284

Artificial Inteligence Strategy Data Machine Learning 284

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Hu's Place - HitachiVantara

JANUARY 15, 2019

This new company will unify the operations of these three companies into a single integrated business as Hitachi Vantara to capitalize on Hitachi’s social innovation capability in both operational technologies (OT) and information technologies (IT).

Systems Review 72

Systems Review Storage System Software Review 72

Kentik

MAY 10, 2023

A unified data repository (UDR) is a centralized storage system that consolidates, organizes, and manages data from different sources. It serves as a single point of access for various types of data, which could be a significant volume of very diverse data formats in an extensive network. Why do we need a UDR?

Analytics 59

Analytics Network Data Machine Learning 59

Altexsoft

FEBRUARY 11, 2023

Data is now one of the most valuable assets for any kind of business. The 11th annual survey of Chief Data Officers (CDOs) and Chief Data and Analytics Officers reveals 82 percent of organizations are planning to increase their investments in data modernization in 2023. Feel free to enjoy it. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

JULY 24, 2023

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

Open Source 65

Open Source Analytics Software Review Metrics 65

CIO

AUGUST 2, 2023

A data and analytics capability cannot emerge from an IT or business strategy alone. With both technology and business organization deeply involved in the what, why, and how of data, companies need to create cross-functional data teams to get the most out of it. Does the data live in one or many clouds?

Data 226

Data Architecture Government Strategy 226

Mobilunity

MAY 8, 2023

Key zones of an Enterprise Data Lake Architecture typically include ingestion zone, storage zone, processing zone, analytics zone, and governance zone. Ingestion zone is where data is collected from various sources and ingested into the data lake. Storage zone is where the raw data is stored in its original format.

Engineering 52

Engineering Data Storage AWS 52

InnovationM

MAY 14, 2023

Introduction As someone who has hands-on experience in constructing and leveraging data lakes, I can attest to the transformative power these repositories hold for organizations grappling with vast amounts of data. These systems ensure high availability and facilitate the storage of massive data volumes.

Data 52

Data Storage Construction Business Intelligence 52

Altexsoft

NOVEMBER 9, 2021

If you want to streamline your procurement and gain more visibility into this process, you have to get hold of available data, analyze it, and extract value to make informed decisions. Manual operations and/or outdated technology aren’t able to provide the required visibility and support your decisions. Procurement and its challenges.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Cloudera

NOVEMBER 1, 2022

A quick trip in the congressional time machine to revisit 2017’s Modernizing Government Technology Act surfaces some of the most salient points regarding agencies’ challenges: The federal government spends nearly 75% of its annual information technology funding on operating and maintaining existing legacy information technology systems.

Cloud 83

Cloud Government Storage Analytics 83

Hu's Place - HitachiVantara

APRIL 11, 2019

Data breaches are common, rogue data sets propagate in silos, and companies’ data technology often isn’t up to the demands put on it." Introducing DataOps Today more customer are focusing on the operational aspects of data rather than on the fundamentals of capturing, storing and protecting data.

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

Kentik

APRIL 12, 2023

Data scientists play a critical role in the DataOps ecosystem, leveraging advanced analytics and machine learning techniques to gain insights from large and complex data sets. DataOps strategies require a robust data infrastructure, including data warehouses, data lakes, caches, and other data storage and processing systems.

Network 52

Network Data Engineering Machine Learning Artificial Inteligence 52

TechCrunch

MAY 18, 2022

Liubimov was a senior engineer at Huawei before moving to Yandex, where he worked as a backend developer on speech technologies and dialogue systems. When asked, Heartex says that it doesn’t collect any customer data and open sources the core of its labeling platform for inspection. Heartex’s dashboard.

Open Source 203

Open Source Weak Development Team Artificial Inteligence Data 203

Tenable

NOVEMBER 3, 2022

When our data engineering team was enlisted to work on Tenable One, we knew we needed a strong partner. While the story of Tenable One is, first and foremost, a technology story, the analytics baked into the platform would not be possible without the ability to ingest and process a wide variety of data from a suite of point tools. .

Data 98

Data AWS Storage Data Engineering 98

Altexsoft

JANUARY 14, 2021

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. For over 30 years, data warehouses have been a rich business-insights source. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

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? The simplest illustration for a data pipeline.

Data 76

Data Storage Analytics Data Center 76

Altexsoft

FEBRUARY 22, 2022

Technological solutions to fleet maintenance. To support your preventive maintenance strategy, you have two technological options. Reporting and analytics is essential to obtain a bird eye view of your fleet and make data-based decisions. It requires building a complex storage, processing, and analysis architecture.

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

NOVEMBER 5, 2021

It employs the REST API design, making it possible for third-party apps to access data stored in HISs. If you’re not familiar with the technological side of data exchange, read the following articles to connect dots: What is EDI: The Main Document Exchange Technology. Data quality management. Source: FHIM.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

O'Reilly Media - Ideas

JANUARY 8, 2019

The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. LinkedIn recently found that demand for data scientists in the US is “off the charts,” and our survey indicated that the demand for data scientists and data engineers is strong not just in the US but globally.

Trends 86

Trends Data Machine Learning Artificial Inteligence 86

Altexsoft

MARCH 18, 2021

It is the process of collecting raw data from disparate sources, transmitting it to a staging database for conversion, and loading prepared data into a unified destination system. The approach is possible thanks to the modern technologies that allow for storing and processing huge volumes of data in any format.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

TIBCO - Connected Intelligence

MARCH 5, 2020

Over the past sixty years, technology has redefined how people live and work, how commerce occurs, how citizens and governments engage, and so much more. With digital transformation critical to every organization’s survival, it makes sense that organizations want to leverage and gain advantage from technology advancements.

Technology 42

Technology Games Trends IoT 42

Hu's Place - HitachiVantara

MAY 10, 2019

In the past 10 years the incidents of fraud have escalated thanks to new technologies, like mobile, that have been adopted by banks to better serve their customers. However, in the rush to do this, many of these systems have been poorly architected to address the total analytics pipeline. This is colloquially called data wrangling.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

Hu's Place - HitachiVantara

MAY 24, 2019

The latest International Data Corporation ( IDC ) Worldwide Quarterly Enterprise Storage Systems Tracker , was published on March 4, 2019. It showed vendor revenue in the worldwide enterprise storage systems market is still increasing: 7.4% enterprise storage market in 4Q 2018. year over year to $14.5 This takes DataOps.

Marketing 75

Marketing Storage Systems Review Enterprise 75