Altexsoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data 87

Data Data Engineering Big Data Architecture 87

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 123

Artificial Inteligence Generative AI Security Applications 123

Altexsoft

OCTOBER 29, 2020

But before you dive in, we recommend you reviewing our more beginner-friendly articles on data transformation: Complete Guide to Business Intelligence and Analytics: Strategy, Steps, Processes, and Tools. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

AWS Machine Learning - AI

JUNE 21, 2024

To accomplish this, eSentire built AI Investigator, a natural language query tool for their customers to access security platform data by using AWS generative artificial intelligence (AI) capabilities. eSentire has over 2 TB of signal data stored in their Amazon Simple Storage Service (Amazon S3) data lake.

Artificial Inteligence 97

Artificial Inteligence Generative AI AWS Serverless 97

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

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

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

Hu's Place - HitachiVantara

JANUARY 3, 2019

Data curation will be a focus to understand the meaning of the data as well as the technologies that are applied to the data so that data engineers can move and transform the essential data that data consumers need to power the organization. However, with great power comes great responsibilities.

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 85

Data Analytics Cloud Technical Review 85

TIBCO - Connected Intelligence

MARCH 5, 2020

The business value of data continues to rise – Every business transformation today—be it greater customer intimacy, more optimized operations, faster innovation, and more—is fueled by data. Data quality remains elusive – Diverse and evolving data definitions, syntax, structures, sources, and uses conspire to limit data efficacy.

Technology 42

Technology Games Trends IoT 42

Cloudera

MAY 22, 2018

With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. This leads to wasted time and effort during research and collaboration or, worse, compliance risk. With release 1.4

Data 42

Data Load Balancer Machine Learning Artificial Inteligence 42

Altexsoft

MARCH 2, 2023

Data quality involves storing data in its correct and consistent form. Here’s a deep dive into data quality management and tools. Data availability is responsible for making data accessible to appropriate personnel within the system. Compliance. Improved data management.

Government 52

Government Tools Data Weak Development Team 52

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. This includes Apache Hadoop , an open-source software that was initially created to continuously ingest data from different sources, no matter its type.

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. Are responsible for designing, managing, and maintaining tools that automate operational processes. Leverage tools to automate AWS networking tasks. AWS Certified Big Data – Speciality.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Mobilunity

NOVEMBER 24, 2021

In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. In this article, we’ll discuss the role of an ETL engineer in data processing and why businesses need such experts nowadays. Who Is an ETL Engineer?

Development 52

Development Storage Recruiting Architecture 52

O'Reilly Media - Ideas

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. Whether you manage customer-facing AI products, or internal AI tools, you will need to ensure your projects are in sync with your business.

Product Management 136

Product Management Artificial Inteligence Machine Learning Weak Development Team 136

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. Cloud data warehouse architecture.

Backup 115

Backup Azure Software Review Architecture 115

Altexsoft

JUNE 6, 2019

Let’s find out how retailers invest in high tech to impress customers in physical stores and use tools to increase efficiency and speed of their operations. Data collected from the robot is processed in a cloud for planogram compliance. Voice activation: shopping with virtual assistants and Theatro tool for retail clerks.

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

Altexsoft

NOVEMBER 9, 2021

To analyze that, you’ll have to collect available data from external sources such as market reports, peer reviews, and public financial statements. Procurement management or analytics tools must integrate with major market information providers as D&B , Cerved , and Bureau van Dijk. Compliance evaluation. Fraud detection.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

O'Reilly Media - Ideas

JANUARY 25, 2024

That change is important because event-driven architecture is a tool for designing large systems that have to ingest data from many different streams in real time. It’s now used in operating systems (Linux kernel components), tool development, and even enterprise software. We also saw 9.8% SQL Server also showed a 5.3%

Trends 111

Trends Technical Review Technology Artificial Inteligence 111

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

Altexsoft

MARCH 16, 2021

In short, this term relates to large amounts of data — both structured and unstructured — that are too voluminous or complex to be processed with traditional software tools. Let’s take a quick look at the big data infrastructure. Big Data infrastructure in healthcare. Big data infrastructure in a nutshell.

Big Data 116

Big Data Healthcare Applications Data 116

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ).

Data 91

Data Analytics Machine Learning Artificial Inteligence 91

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

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

Altexsoft

JULY 19, 2022

As the picture above clearly shows, organizations have data producers and operational data on the left side and data consumers and analytical data on the right side. Data producers lack ownership over the information they generate which means they are not in charge of its quality. It works like this.

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

DECEMBER 4, 2020

You can read more about it in our previous article Data Migration: Process, Types, and Golden Rules to Follow. Here, we’ll focus on tools that can save you the lion’s share of tedious tasks — namely, key types of data migration software, selection criteria, and some popular options available in the market. Self-scripted tools.

Software Review 69

Software Review Software Data Technical Review 69

Cloudera

AUGUST 24, 2020

Next you need to understand your data , cataloging enterprise data into business and compliance terms. The most relevant use cases are those that use or integrate data, including publicly available data, and you combine that with your internal data.

Cloud 82

Cloud Data Government Innovation 82

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. To avoid errors that may threaten patient safety, AHIMA introduced the data quality management model which covers. Supported data formats.

Technical Review 59

Technical Review Technology Software Review Healthcare 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. Third, you need to do more research.

Virtualization 69

Virtualization Data How To Data Engineering 69

Cloudera

NOVEMBER 13, 2017

Cloud PaaS takes this a step further and allows users to focus directly on building data pipelines, training machine learning models, developing analytics applications — all the value creation efforts, vs the infrastructure operations. The net result is much improved productivity for data engineers, data scientists, and analysts.

Analytics 40

Analytics Cloud Big Data Machine Learning 40

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

JANUARY 11, 2021

Cloudera Data Warehouse (CDW) is a cloud service and an integral part of the newly released Cloudera Data Platform (CDP). Key features are: Highly scalable and performant open-source engines for BI and data warehousing workloads. Separate compute from storage. Data can be served to the business with ease.

Data 64

Data Pharmaceuticals Open Source Machine Learning 64

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. A REST API is built directly into our VSP storage controllers.

Systems Review 72

Systems Review Storage System Software Review 72

Altexsoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Altexsoft

MARCH 14, 2023

In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support. This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. What is a modern data stack?

Data 59

Data Technical Review Software Review Open Source 59