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

Altexsoft

SEPTEMBER 9, 2022

Efficient metadata management ensures data integrity , consistency, trustworthiness, and compliance. To ensure metadata quality as well as correct application of metadata policies and proper compliance to requirements and standards, audits have to be regularly conducted by data stewards. Let’s explore what they are.

Tools 59

Tools Technical Review Software Review Systems Review 59

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

OCTOBER 15, 2020

Towards these trends, our clients have significantly invested in data-related technologies and talent over the past several years, including: Data governance to cater to enterprise-level financial reporting and regulatory compliance as an example. Self-service data discovery (e.g.,

Virtualization 50

Virtualization Data Energy Innovation 50

O'Reilly Media - Ideas

NOVEMBER 13, 2018

As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. Let’s begin by looking at the state of adoption.

Machine Learning 92

Machine Learning Artificial Inteligence Software Review Conference 92

O'Reilly Media - Ideas

FEBRUARY 11, 2019

The resource examples I’ll cite will be drawn from the upcoming Strata Data conference in San Francisco , where leading companies and speakers will share their learnings on the topics covered in this post. AI and machine learning in the enterprise. AI and machine learning in the enterprise. Foundational data technologies.

Big Data 87

Big Data Technology Tools Cloud 87

Cloudera

DECEMBER 10, 2020

CDW includes two highly scalable and performant Apache open-source engines – Impala and Hive LLAP – that have proven themselves in hundreds of enterprises for business-critical data warehousing. Today, enterprises want data warehouses that support on-demand consumption.

Data 98

Data Technical Review Storage Systems Review 98

Lacework

NOVEMBER 1, 2023

When architecting data systems, a key philosophy is keeping customer privacy front and center both in the design choices made and and options presented to the user, while ensuring the ability to meet business needs and service criteria. What is privacy? A mart is a group of aggregated tables (e.g.,

System Design 52

System Design Systems Review System Data 52

DataRobot

MARCH 10, 2022

DataRobot and Snowflake Jointly Unleash Human and Machine Intelligence Across the Industrial Enterprise Landscape. Python is unarguably the most broadly used programming language throughout the data science community. The “Fourth Industrial Revolution” was coined by Klaus Schwab of the World Economic Forum in 2016.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 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

MAY 22, 2018

Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. This leads to wasted time and effort during research and collaboration or, worse, compliance risk.

Data 42

Data Load Balancer Machine Learning Artificial Inteligence 42

Cloudera

NOVEMBER 12, 2020

Typically, when we talk about data warehousing at an enterprise level on the cloud, one of the biggest concerns is that moving workloads from on-premises to the cloud is not seamless and opens up new risks for data safety and security. The last thing you need is another 1-3 month analysis project.

Data Center 103

Data Center Cloud Data Policies 103

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. . They quickly met the full range of enterprise needs starting from SaaS to PaaS and IaaS. Security, identity, and compliance. What aspects often turn out to be decisive?

Azure 52

Azure AWS Cloud How To 52

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

O'Reilly Media - Ideas

MARCH 31, 2020

It may even be necessary to do image or video analysis to make content-based recommendations, detect fraud, or reject content that violates your rules (for example, live shooter videos). The need for an experimental culture implies that machine learning is currently better suited to the consumer space than it is to enterprise companies.

Product Management 139

Product Management Artificial Inteligence Machine Learning Software Review 139

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. One-sixth of respondents identify as data scientists, but executives—i.e., Model degradation is the No.

Enterprise 134

Enterprise Survey Technical Review Weak Development Team 134

CIO

AUGUST 18, 2022

Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. The result is an emerging paradigm shift in how enterprises surface insights, one that sees them leaning on a new category of technology architected to help organizations maximize the value of their data.

Data 350

Data Artificial Inteligence Technical Advisors Technical Review 350

O'Reilly Media - Ideas

JANUARY 25, 2024

Our data shows that most topics in software architecture and design are down year-over-year. While software architecture is down 3.9% (a relatively small decline), enterprise architecture is up 8.9%. Domain-driven design is particularly useful for understanding the behavior of complex enterprise systems; it’s down, but only 2.0%.

Trends 118

Trends Technical Review Technology Artificial Inteligence 118

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

DataRobot

MARCH 16, 2023

To work effectively, data scientists need agility in the form of access to enterprise data, streamlined tooling, and infrastructure that just works. Agility and enterprise security, compliance, and governance are often at odds. They work with partners in IT to harden ML use cases into production systems.

Data 52

Data Machine Learning Artificial Inteligence Agile 52

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. The primary difference resides in WHERE and WHEN data transformation and loading happens. These are data engineers who are responsible for implementing these processes.

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. For individuals who perform complex Big Data analyses and have at least two years of experience using AWS. Implement core AWS Big Data services according to basic architecture best practices.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Altexsoft

MARCH 2, 2023

As the amount of enterprise data continues to surge, businesses are increasingly recognizing the importance of data governance — the framework for managing an organization’s data assets for accuracy, consistency, security, and effective use. Projections show that the data governance market will expand from $1.81

Government 52

Government Tools Data Weak Development Team 52

Cloudera

OCTOBER 25, 2022

Enabling data and analytics in the cloud allows you to have infinite scale and unlimited possibilities to gain faster insights and make better decisions with data. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Cloud 52

Cloud Data Firewall AWS 52

John Snow Labs

MAY 24, 2023

The two important functions of this tool are: – Performing different types of labeling with various data formats. LabelBox LabelBox is an efficient AI Data Engine platform for AI assisted labeling, data curation, model training, and more. It annotates images, videos, text documents, audio, and HTML, etc.

Tools 52

Tools Machine Learning Artificial Inteligence Software Review 52

Altexsoft

JANUARY 14, 2021

A data warehouse is defined as a centralized repository where a company stores all valuable data assets integrated from different channels like databases, flat files, applications, CRM systems, etc. A data warehouse is often abbreviated as DW or DWH. You may also find it under the name of an enterprise data warehouse (EDW).

Backup 115

Backup Azure Software Review Systems Review 115

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

BPM

JANUARY 18, 2019

That augmentation must be in a form attractive to humans while enabling security, compliance, authenticity and auditability. Process mining will be incorporated into larger suites of professional business process analysis tools. This will aid the faster creation of baseline models, enabling analysis and process improvement.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Altexsoft

JULY 19, 2022

Through all these shifts, data mesh is called to solve the problems of centralized data platforms by giving more flexibility and independence, agility and scalability, cost-effectiveness, and cross-functionality. Data mesh principles and architecture. And it’s their job to guarantee data quality. It works like this.

Architecture 52

Architecture Data Analytics Data Engineering 52

Cloudera

JUNE 4, 2018

Ensure content can be reused within the data hub to support pharmaceutical use cases. Aspire , built by Search Technologies , part of Accenture is a search engine independent content processing framework for handling unstructured data. This enables data hub users to quickly access up-to-date content across the enterprise.

Pharmaceuticals 47

Pharmaceuticals Data Big Data Systems Review 47

Altexsoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Virtualization 69

Virtualization Tools Data Architecture 69

TIBCO - Connected Intelligence

DECEMBER 20, 2021

TIBCO Cloud Integration was identified as a “Leader” in four analyst reports, including the 2021 Gartner ® Magic Quadrant for EiPaaS , the Forrester Wave Enterprise iPaaS, Q4, 2021 , the 2021 Nucleus Research iPaaS Value Matrix , and the 2021 Aragon Research Globe Digital Business Business Platform Report.

Innovation 26

Innovation Analytics Virtualization Cloud 26

Altexsoft

AUGUST 22, 2022

The landscape of enterprise data is fragmented. Organizations have data stored in public and private clouds, as well as in various on-premises data repositories. Some would say that it’s not a big deal, however, these mixed environments have resulted in the complexities of managing disjointed data and business processes.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52

Altexsoft

NOVEMBER 10, 2021

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. Typically used for data analysis and reporting, data warehouses rely on ETL mechanisms to extract , transform , and load data into a destination.

Architecture 52

Architecture Data Storage Machine Learning 52

O'Reilly Media - Ideas

MARCH 1, 2023

Governance (year-over-year increase of 72%) is a very broad topic that includes virtually every aspect of compliance and risk management. Data Data is another very broad category, encompassing everything from traditional business analytics to artificial intelligence. This is a trend worth watching.

Trends 136

Trends Technical Review Technology Software Review 136

O'Reilly Media - Ideas

JANUARY 25, 2022

While our customers include many individual developers, contractors, and hobbyist programmers, commercial (enterprise) software developers are very heavily represented—although there are certainly areas into which we’d like more visibility, such as the crucial Asia-Pacific software development community.

Trends 110

Trends Technical Review Technology Artificial Inteligence 110

Altexsoft

MARCH 30, 2023

But what do the gas and oil corporation, the computer software giant, the luxury fashion house, the top outdoor brand, and the multinational pharmaceutical enterprise have in common? The answer is simple: They use the same technology to make the most of data. How data engineering works in 14 minutes.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64