Altexsoft

FEBRUARY 11, 2023

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. What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority.

Data 87

Data Data Engineering Big Data Architecture 87

Hu's Place - HitachiVantara

JANUARY 3, 2019

Public cloud, agile methodologies and devops, RESTful APIs, containers, analytics and machine learning are being adopted. ” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Xebia

MARCH 10, 2021

Therefore these organisations introduce a new capability: Data & Analytics. This blog elaborates on how adopting DevOps principles can enhance business value creation for the world of Data & Analytics. Data & Analytics as a separate business domain. a data & analytics platform).

DevOps 130

DevOps Data Analytics Policies 130

Cloudera

JANUARY 27, 2021

Achieving SOC 2 is one of the first milestones on our aggressive security and compliance roadmap. You can expect to see further compliance achievements, including expanding Cloudera’s ISO27001 certification to include CDP Public Cloud, FedRAMP, and more, over the coming quarters. Why is SOC 2 Important?

Cloud 101

Cloud Disaster Recovery Software Review Technical Review 101

Capgemini

MAY 28, 2020

Companies know they need to integrate artificial intelligence into the manufacturing process, but the real challenge continues to be achieving it at scale. Scaling artificial-intelligence implementations beyond the proof-of-concept (PoC) level remains one of the biggest hurdles.

Artificial Intelligence 52

Artificial Intelligence Artificial Inteligence Automotive Data Engineering 52

Cloudera

JANUARY 19, 2018

Machine Learning in the Age of Big Data. Sean Anderson provides a tutorial on machine learning. From its origins in the 1950’s to today, the age of big data. Sean ascertains that larger data sets and increased access to compute power is propelling the adoption of machine learning.

Artificial Inteligence 45

Artificial Inteligence Machine Learning Big Data IoT 45

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.

Architecture 52

Architecture Data Storage Machine Learning 52

Cloudera

NOVEMBER 1, 2022

In the private sector, excluding highly regulated industries like financial services, the migration to the public cloud was the answer to most IT modernization woes, especially those around data, analytics, and storage. The source and availability of every material and part across each branch is an opportunity for risk.

Cloud 83

Cloud Government Storage Analytics 83

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Deep Learning.

Big Data 85

Big Data Technology Tools Cloud 85

O'Reilly Media - Ideas

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. Machine learning adds uncertainty.

Product Management 136

Product Management Artificial Inteligence Machine Learning Software Review 136

InnovationM

MAY 14, 2023

They help establish data lineage, enable data discovery, and enforce compliance with data governance policies. Metadata management tools ensure a clear understanding of the data landscape and enhance data stewardship practices.

Data 52

Data Storage Construction Business Intelligence 52

Cloudera

MAY 10, 2018

Click to tweet : Nominations are now open for the sixth annual Cloudera Data Impact Awards! With advancements in exploratory data science, machine learning, predictive analytics, AI, and data engineering, the world is increasingly driven by data. Enterprise machine learning.

Data 41

Data Machine Learning Artificial Inteligence Data Engineering 41

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

REAN Cloud is a global cloud systems integrator, managed services provider and solutions developer of cloud-native applications across big data, machine learning and emerging internet of things (IoT) spaces. This April, 47Lining, announced its Amazon Web Services (AWS) Industrial Time Series Data Connector Quick Start.

Cloud 78

Cloud Google Cloud Azure AWS 78

Cloudera

AUGUST 31, 2021

Data warehousing is the backbone of every data driven organization , providing mission critical analytics. Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Copyright © 2021 Accenture. All rights reserved.

Data 80

Data Analytics Cloud Technical Review 80

Capgemini

NOVEMBER 14, 2022

And they also need to trust that the data is current, relevant, and available. Moving a business forward requires fast access to good data for more applications. But that turns IT and analytics teams into the bottleneck. For self-service BI to succeed, however, the entire data value chain may need to be fixed.

Agile 52

Agile Technical Review Systems Review Artificial Intelligence 52

Altexsoft

SEPTEMBER 9, 2022

In data science , metadata is one of the central aspects: It describes data (including unstructured data streams) fed into a big data analytical platform, capturing, for example, formats, file sizes, source of information, permission details, etc. Alation: support for self-service analytics and BI.

Tools 59

Tools Technical Review Software Review Systems Review 59

Erik Bernhardsson

OCTOBER 27, 2015

So I learned something very useful about communication and promoting your ideas. What advice do you have to younger analytics professionals and in particular PhD students in the Sciences? So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering. Don’t watch TV :).

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

So I learned something very useful about communication and promoting your ideas. What advice do you have to younger analytics professionals and in particular PhD students in the Sciences? So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering. Don’t watch TV :).

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

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. What is procurement analytics and the opportunities it offers? Main components of procurement analytics. Procurement and its challenges.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Existek

JANUARY 11, 2022

The cloud computing market covers many areas like business processes, infrastructure, platform, security, management, analytics supported by cloud providers. 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

CIO

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. You can intuitively query the data from the data lake.

Data 350

Data Artificial Inteligence Technical Advisors Technical Review 350

Altexsoft

FEBRUARY 8, 2021

These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development. Optimization opportunities offered by analytics.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

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

Cloudera

DECEMBER 10, 2020

CDW’s engines such as Impala and Hive low-latency analytical processing (LLAP) directly operate on extremely compact open file formats, such as Parquet and ORC. These file formats not only help avoid data duplication into proprietary storage formats but also provide highly efficient storage formats.

Data 98

Data Technical Review Storage Systems Review 98

Altexsoft

JUNE 11, 2021

an also be described as a part of business process management (BPM) that applies data science (with its data mining and machine learning techniques) to dig into the records of the company’s software, get the understanding of its processes performance, and support optimization activities. Process analytics takes place.

Applications 69

Applications Weak Development Team Systems Review Software Review 69

Cloudera

FEBRUARY 19, 2018

Running a large company is impossible without having an ERP system in place, and SAP business software remains at the forefront in this category. But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough. Governance.

Data 46

Data Government Big Data Compliance 46

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 82

Insurance Compliance Technical Review Banking 82

Cloudera

OCTOBER 1, 2022

According to Gartner, by 2023 65% of the world’s population will have their personal data covered under modern privacy regulations. . As a result, growing global compliance and regulations for data are top of mind for enterprises that conduct business worldwide. People selling information.

Government 71

Government Artificial Inteligence Enterprise Strategy 71

Cloudera

OCTOBER 19, 2023

This exponential growth in connected devices will force telcos to up their game, first by provisioning the capacity they need to scale and maintain next-gen 5G data networks, and later by improving the effectiveness of their data management and governance practices.

Data 73

Data Compliance Architecture Data Engineering 73

Cloudera

AUGUST 30, 2022

Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Data quality issues deter trust and hinder accurate analytics. Disparate systems create issues with transparency and compliance. Towards Data Science ). Deploying modern data architectures.

Architecture 75

Architecture Data Artificial Inteligence Artificial Intelligence 75

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Enhanced multi-function analytics. Accelerate analytics with materialized view support.

Cloud 76

Cloud Data Analytics Machine Learning 76

BPM

JANUARY 18, 2019

The current Artificial Intelligence (AI) fascination is unfortunately completely biased on Deep Neural Networks (DNN) and Machine Learning (ML) for everything. That augmentation must be in a form attractive to humans while enabling security, compliance, authenticity and auditability. Denis Gagne Trisotech [link].

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

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. Or so they all claim.

Cloud 107

Cloud Data Compliance Government 107

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 83

Data Analytics Machine Learning Artificial Inteligence 83

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” According to Gartner, Inc.

Architecture 96

Architecture Innovation Data Machine Learning 96

Cloudera

NOVEMBER 13, 2017

As the market moves toward cloud-based big data and analytics, three qualities emerge as vital for success. End-user focused tools accelerate daily tasks like job submission, performance tuning, and workload analytics. Intelligent defaults and built-in logic eliminate much of the guess work. We’re here to help.

Analytics 40

Analytics Cloud Big Data Machine Learning 40

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. These are data engineers who are responsible for implementing these processes. Data size and type. ELT comes to the rescue. What is ELT?

Systems Review 109

Systems Review Technical Review Software Review Compliance 109