Cloudera

DECEMBER 10, 2020

Some data warehousing solutions such as appliances and engineered systems have attempted to overcome these problems, but with limited success. . Recently, cloud-native data warehouses changed the data warehousing and business intelligence landscape. The time IT spends on maintaining the data is greatly reduced.

Data 98

Data Technical Review Storage Systems Review 98

Altexsoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

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

Cloudera

NOVEMBER 12, 2020

Most of our customers’ data centers struggle to keep up with their dynamic, ever-increasing business demands. The two examples listed here represent a quick glance at the challenges customers face due to the peak demands and extreme pressure on their data centers. The last thing you need is another 1-3 month analysis project.

Data Center 103

Data Center Cloud Data Policies 103

O'Reilly Media - Ideas

NOVEMBER 13, 2018

In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. As noted above, fairness audits will require a mix of data and domain experts.

Machine Learning 92

Machine Learning Artificial Inteligence Software Review Conference 92

Hu's Place - HitachiVantara

JANUARY 3, 2019

” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared. 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

Altexsoft

OCTOBER 29, 2020

When data is subjective and accurate, it gives us a better understanding than we can fathom with our human brains. Because as any system, data processing is subject to mistakes. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

Existek

JANUARY 11, 2022

It might be challenging as it requires a detailed analysis of the business-specific needs and a deeper understanding of the overall market situation. . For example, they considerably revised the cloud strategy due to the need to transform the delivery model from PaaS to IaaS, thus renaming Windows Azure to Microsoft Azure in 2014. .

Azure 52

Azure AWS Cloud How To 52

Altexsoft

FEBRUARY 8, 2021

The data that your procurement management software generates can help you analyze potential suppliers’ performance by comparing their KPIs, prices, compliance, and other variables. For example, you can see that the machine breakdown increased, and the root cause analysis shows that it happened because of cheaper spare parts or fuel.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Cloudera

FEBRUARY 15, 2024

While there are clear reasons SVB collapsed, which can be reviewed here , my purpose in this post isn’t to rehash the past but to present some of the regulatory and compliance challenges financial (and to some degree insurance) institutions face and how data plays a role in mitigating and managing risk.

Insurance 88

Insurance Compliance Technical Review Banking 88

DataRobot

MARCH 10, 2022

These initiatives utilize interconnected devices and automated machines that create a hyperbolic increase in data volumes. This type of growth has stressed legacy data management systems and makes it nearly impossible to implement a profitable data-centered solution.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

O'Reilly Media - Ideas

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Imagine you are a data scientist at Disney.

Product Management 139

Product Management Artificial Inteligence Machine Learning Software Review 139

Altexsoft

NOVEMBER 9, 2021

Accounts payable are most vulnerable to errors (whether deliberate or not) due to disconnected and inaccurate information, especially if you have to deal with a big amount of documentation and process multiple transactions. The market is constantly changing due to a myriad of factors. Contract management to review and audit agreements.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

CIO

AUGUST 18, 2022

Enter the data lakehouse. Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). Under Guadagno, the Deerfield, Ill.-based

Data 350

Data Artificial Inteligence Technical Advisors Technical Review 350

Altexsoft

MARCH 18, 2021

ETL and ELT are the most widely applied approaches to deliver data from one or many sources to a centralized system for easy access and analysis. With ETL, data is transformed in a temporary staging area before it gets to a target repository (e.g Both consist of the extract, transform, and load stages. What is ETL?

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

O'Reilly Media - Ideas

JANUARY 25, 2024

And the real question that will change our industry is “How do we design systems in which generative AI and humans collaborate effectively?” Domain-driven design is particularly useful for understanding the behavior of complex enterprise systems; it’s down, but only 2.0%. So the software development world is changing. We also saw 9.8%

Trends 118

Trends Technical Review Technology Artificial Inteligence 118

Altexsoft

MARCH 16, 2021

It’s referred to as big data, since, for example, just a single complete human genome sequence produces about 200 Gb of raw data. Now, we know where big data in healthcare originates. Let’s take a quick look at the big data infrastructure. Big Data infrastructure in healthcare. Big Data in epidemiology.

Big Data 116

Big Data Healthcare Applications Data 116

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

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. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

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

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. Data analysis, transformation, and decision support revolve around deriving knowledge and insights critical for enhancing patient care.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

O'Reilly Media - Ideas

MARCH 18, 2020

More than half of respondent organizations identify as “mature” adopters of AI technologies: that is, they’re using AI for analysis or in production. One-sixth of respondents identify as data scientists, but executives—i.e., What is more, almost three-quarters of survey respondents say they work with data in their jobs.

Enterprise 134

Enterprise Survey Technical Review Weak Development Team 134

Altexsoft

MARCH 2, 2023

Data governance is a broad term that refers to a critical set of organizational policies, processes, roles, standards, and metrics for ensuring the accuracy, consistency, security, and availability of data as well as its effective use. Data quality involves storing data in its correct and consistent form. Compliance.

Government 52

Government Tools Data Weak Development Team 52

O'Reilly Media - Data

MARCH 22, 2018

There is often a need to verify the reasoning of such ML systems to hold algorithms accountable for the decisions predicted. But, in some scenarios, such as credit scoring or the judicial system , models have to be both highly accurate and understandable. Exploratory data analysis and visualization.

Off-The-Shelf 115

Off-The-Shelf Machine Learning Artificial Inteligence Weak Development Team 115

Altexsoft

NOVEMBER 10, 2021

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store.

Architecture 52

Architecture Data Storage Machine Learning 52

Cloudera

JUNE 4, 2018

Unstructured content lacks a predefined data model; it must first undergo text extraction, classification, and enrichment to provide intelligence. the client needed an approach to: Simplify data hub ingestion, especially for large volumes of unstructured content. compliance reporting.

Pharmaceuticals 47

Pharmaceuticals Data Big Data Systems Review 47

Altexsoft

AUGUST 22, 2022

A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., to provide a unified view of all enterprise data.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52

O'Reilly Media - Ideas

MARCH 1, 2023

Two smaller categories that are closely related to coding practices also showed substantial increases: usage of content about Git (a distributed version control system and source code repository) was up 21%, and QA and testing was up 78%. As our systems are growing ever larger, object-oriented programming’s importance seems secure.

Trends 136

Trends Technical Review Technology Software Review 136

Agile Engine

DECEMBER 27, 2023

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7. Table of contents 1.

Big Data 52

Big Data Analytics Data Analysis 52

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. 2018 was a very busy year for Hitachi Vantara.

Systems Review 72

Systems Review Storage System Software Review 72

O'Reilly Media - Ideas

JANUARY 25, 2022

For example, interest in security, after being steady for a few years, has suddenly jumped up, partly due to some spectacular ransomware attacks. Our approach to Answers was to do a simple “bag of words” analysis: count the number of times each word was used in all Answers queries. Usage of general content also increased.

Trends 110

Trends Technical Review Technology Artificial Inteligence 110

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

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. Data democratization.

Data 59

Data Technical Review Software Review Artificial Inteligence 59