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

AWS Machine Learning - AI

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices.

Artificial Inteligence 126

Artificial Inteligence Generative AI Security Applications 126

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

Cloudera

DECEMBER 10, 2020

Generally, if five LOB users use the data warehouse on a public cloud for eight hours a day for one month, you pay for the use of the service and the associated cloud hardware resources (compute and storage) for this period. 150 for storage use = $15 / TB / month x 10 TB. 150 for storage use = $15 / TB / month x 10 TB.

Data 98

Data Technical Review Storage Systems Review 98

AWS Machine Learning - AI

JUNE 21, 2024

eSentire has over 2 TB of signal data stored in their Amazon Simple Storage Service (Amazon S3) data lake. This further step updates the FM by training with data labeled by security experts (such as Q&A pairs and investigation conclusions).

Artificial Inteligence 101

Artificial Inteligence Generative AI AWS Serverless 101

Mentormate

OCTOBER 31, 2023

The allure of the latest machine-learning techniques is undeniable, but without a well-structured approach, you risk getting lost in the technological maze. In the world of AI, success hinges not only on technological prowess but also on aligning your solutions with the broader business strategy.

Artificial Inteligence 98

Artificial Inteligence Healthcare Budget Training 98

Hu's Place - HitachiVantara

JANUARY 3, 2019

In order to utilize the wealth of data that they already have, companies will be looking for solutions that will give comprehensive access to data from many sources. More focus will be on the operational aspects of data rather than the fundamentals of capturing, storing and protecting data.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data 86

Data Analytics Cloud Technical Review 86

Existek

JANUARY 11, 2022

In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2. They provided a few services like computing, Azure Bob storage, SQL Azure, and Azure Service Bus. The new structure enabled the opportunity to meet such customer needs in computing as storage, networking, and services.

Azure 52

Azure AWS Cloud How To 52

Altexsoft

SEPTEMBER 9, 2022

Metadata management is a set of activities, technologies, and policies that target metadata collection, storage, and organizing. It aims at making data assets understandable and discoverable for users. Metadata storage usually implies developing a specialized repository. Metadata storage.

Tools 59

Tools Technical Review Software Review Systems Review 59

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. We’re skeptical about things like job displacement, at least in technology. This has been a strange year. What will those changes be?

Trends 111

Trends Technical Review Technology Artificial Inteligence 111

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Cloud-based spending will reach 60% of all IT infrastructure and 60-70% of all software, services, and technology spending by 2020. In 2019, CIOs will have to optimize applications of the newest cloud technology in response to their requirements.

Cloud 78

Cloud Google Cloud Azure AWS 78

Altexsoft

NOVEMBER 5, 2021

So, we’ll only touch on its most vital aspects, instruments, and areas of interest — namely, data quality, patient identity, database administration, and compliance with privacy regulations. It employs the REST API design, making it possible for third-party apps to access data stored in HISs. Data quality management.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Cloudera

SEPTEMBER 14, 2020

Everybody needs more data and more analytics, with so many different and sometimes often conflicting needs. Data engineers need batch resources, while data scientists need to quickly onboard ephemeral users. Fundamental principles to be successful with Cloud data management.

Cloud 111

Cloud Data Compliance Analytics 111

Altexsoft

JUNE 6, 2019

For this article, we discussed current and potential applications of AI in retail, as well as the state of the industry in general, including factors that drive adoption of cognitive technologies. The JD stores use RFID (radio frequency identification), facial recognition, and image recognition technology to monitor retail activity.

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

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

ParkMyCloud

JANUARY 17, 2020

Additionally, they must be able to implement and automate security controls, governance processes, and compliance validation. Intended for individuals that have an expertise in network, compute, security and storage so that they can design solutions that run on Azure. Azure DevOps Engineer Expert. Azure Data Engineer Associate.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Cloudera

DECEMBER 15, 2022

With CDP, customers can deploy storage, compute, and access, all with the freedom offered by the cloud, avoiding vendor lock-in and taking advantage of best-of-breed solutions. This enables a range of data stewardship and regulatory compliance use cases. Read why the future of data lakehouses is open.

Cloud 83

Cloud Data Analytics Machine Learning 83

Altexsoft

MARCH 16, 2021

Check our article on data engineering to get a detailed understanding of the data pipeline and its components. Big data infrastructure in a nutshell. To deliver valuable, applicable knowledge, data has to go through the following stages of a data pipeline: Big data sources continuously generate raw, real-world data.

Big Data 116

Big Data Healthcare Applications Data 116

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. Is it still so? Scalability opportunities.

Backup 115

Backup Azure Architecture Software Review 115

Altexsoft

NOVEMBER 9, 2021

Manual operations and/or outdated technology aren’t able to provide the required visibility and support your decisions. It’s usually used to adjust existing predictions within fast-changing markets such as innovative technology. Compliance evaluation. Invoice and payment analytics to detect errors, compliance issues, and fraud.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Cloudera

AUGUST 30, 2022

Agencies are plagued by a wide range of data formats and storage environments—legacy systems, databases, on-premises applications, citizen access portals, innumerable sensors and devices, and more—that all contribute to a siloed ecosystem and the data management challenge. . Deploying modern data architectures.

Architecture 83

Architecture Data Artificial Inteligence Artificial Intelligence 83

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

O'Reilly Media - Ideas

MARCH 31, 2020

You need to understand that many solutions can’t be bought (yet), that AI products require collaboration between teams, that data silos stand in the way of success, and that the best remedy for failure is picking yourself up and trying again. (To If you can’t walk, you’re unlikely to run. How do you select what to work on?

Product Management 136

Product Management Artificial Inteligence Machine Learning Weak Development Team 136

Altexsoft

MARCH 2, 2023

Data management is a technical implementation of data governance and involves the practical aspects of working with data, such as data storage, retrieval, and analysis. Compliance. Data governance provides a platform for meeting government regulations like GDPR or HIPAA. Improved data management.

Government 52

Government Tools Data Weak Development Team 52

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. It’s a critical part of your security posture and your first line of defense.

Cloud 52

Cloud Data Firewall AWS 52

Altexsoft

JULY 19, 2022

No matter how ridiculous it may sound, the famous quote is applicable to the technology world in many ways. In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. What data mesh is and is not.

Architecture 52

Architecture Data Analytics Data Engineering 52

Datavail

MARCH 10, 2022

Data stewards – provide oversight of data sets to maintain data integrity and ensure implementation of policies from the committee and end-user compliance with the policies. Others – data modelers, data engineers, data architects, and data quality analysts also contribute to the DG process.

Government 40

Government Strategy Weak Development Team Company 40

Altexsoft

NOVEMBER 10, 2021

A data lakehouse , as the name suggests, is a new data architecture that merges data warehouse and data lake into a single whole, aiming at addressing each one’s limitations. In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes.

Architecture 52

Architecture Data Storage Machine Learning 52

Cloudera

AUGUST 24, 2020

Today we are continuing our discussion with Martin Mannion , EMEA Big Data Community lead at Deloitte and Paul Mackay, the EMEA Cloud Lead at Cloudera to look at why security and governance requirements must be tackled in the early stages of data-led use case development, thereby mitigating more work later on. Thanks for joining us.

Cloud 83

Cloud Data Government Innovation 83

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. Strategize on how the right approach and right technology can make data in the cloud your most important asset.

Analytics 40

Analytics Cloud Big Data Machine Learning 40

Cloudera

DECEMBER 7, 2017

Cloud service providers now offer a plethora of “house brand” analytics services, some brand new, some re-purposed versions of older technologies. As each new service is started, data is typically copied in for analysis. That data may be stored multiple times in different pools, each multiplying storage resource costs.

Data 41

Data Machine Learning Artificial Inteligence Analytics 41

Altexsoft

DECEMBER 4, 2020

Businesses can no longer count on using the same technologies for decades. 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

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. Lower project costs are an additional time-to-solution benefit.

Virtualization 69

Virtualization Data How To Data Engineering 69

Cloudera

JUNE 4, 2018

The solution to this massive data challenge embedded the Aspire Content Processing Framework into the Cloudera Enterprise Data Hub as a Cloudera Parcel – a binary distribution format containing the program files, along with additional metadata used by Cloudera Manager. compliance reporting.

Pharmaceuticals 47

Pharmaceuticals Data Big Data Systems Review 47

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

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Engineering 99

Data Engineering Engineering Data Cloud 99