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. It’s here where the private cloud delivers.

Cloud 83

Cloud Government Storage Analytics 83

TIBCO - Connected Intelligence

APRIL 15, 2021

Data and analytics investments pay off. According to McKinsey, “High-performing organizations are three times more likely than others to say their data and analytics initiatives have contributed at least 20 percent to EBIT.” Twenty percent of earnings before interest and taxes from data and analytics alone!

Analytics 41

Analytics Development Team Review Technical Review Data 41

Cloudera

DECEMBER 1, 2017

Vinithra Varadharajan , Philip Langdale , Jason Wang , and Fahd Siddiqui lead a deep dive into running data engineering workloads in a managed service capacity in the public cloud, highlighting cloud infrastructure best practices and illustrating how data engineering workloads interoperate with data analytic engines.

Big Data 40

Big Data Data Cloud Government 40

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

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. Temporal data and time-series analytics.

Big Data 85

Big Data Technology Tools Cloud 85

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. Types of metadata. There are multiple ways to categorize metadata.

Tools 59

Tools Technical Review Software Review Systems Review 59

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. Happy New Year and welcome to 2019, a year full of possibilities.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Cloudera

DECEMBER 10, 2020

CDW is built on top of CDP and has many cutting edge features to provide an excellent data warehousing user experience. For an overview of CDW’s architecture, see DW Built for the cloud. CDW architecture is elastic and simplifies capacity planning. Data Inc realizes cost savings through efficient compute cycles in CDW.

Data 98

Data Technical Review Storage Systems Review 98

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

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

TIBCO - Connected Intelligence

OCTOBER 15, 2020

For instance: How will this new capability impact my client’s as-is and future architectures? 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.

Virtualization 50

Virtualization Data Energy Innovation 50

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

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 96

Architecture Innovation Data Machine Learning 96

Cloudera

AUGUST 30, 2022

Data quality issues deter trust and hinder accurate analytics. Disparate systems create issues with transparency and compliance. Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs).

Architecture 75

Architecture Data Artificial Inteligence Artificial Intelligence 75

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

JUNE 11, 2021

Process analytics takes place. Here, KPIs can be created and monitored to uncover potential improvement areas, data mining and/or ML algorithms can be used to detect hidden patterns and dependencies, or conformance checking techniques can be applied to compare the process to a certain ideal model. Consider predictive analytics.

Applications 69

Applications Weak Development Team Systems Review Software Review 69

Cloudera

OCTOBER 19, 2023

While navigating so many simultaneous data-dependent transformations, they must balance the need to level up their data management practices—accelerating the rate at which they ingest, manage, prepare, and analyze data—with that of governing this data.

Data 73

Data Compliance Architecture Data Engineering 73

TIBCO - Connected Intelligence

JUNE 16, 2021

From strategy, architecture, and design to system integration, we work with clients to identify and realize opportunities to increase their return on investment, improve productivity, and enhance their relationships. Compliance: Use data and analytics to demonstrate contractual, regulatory, and internal audit compliance.”

Data 29

Data Weak Development Team Virtualization Compliance 29

Altexsoft

JULY 19, 2022

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. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two. What data mesh IS.

Architecture 52

Architecture Data Analytics Data Engineering 52

Erik Bernhardsson

OCTOBER 27, 2015

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. How do you respond when you hear the phrase ‘big data’? Write a ton of code. Don’t watch TV :).

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

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. How do you respond when you hear the phrase ‘big data’? Write a ton of code. Don’t watch TV :).

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

DataRobot

MARCH 10, 2022

With Snowflake’s newest feature release, Snowpark , developers can now quickly build and scale data-driven pipelines and applications in their programming language of choice, taking full advantage of Snowflake’s highly performant and scalable processing engine that accelerates the traditional data engineering and machine learning life cycles.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 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

Cloudera

NOVEMBER 12, 2020

Traditional on-premise architectures, which create a fixed, finite set of resources, forces every business request for new insight to be a crazy resource balancing act, coupled with long wait times, or a straight-up no, it cannot be done. A tale of two organizations. We see it everywhere. Key areas of concern are: .

Data Center 101

Data Center Cloud Data Policies 101

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

TIBCO - Connected Intelligence

DECEMBER 7, 2021

While data-driven organizations have more information to work with than ever before, this also means dealing with more data sources, siloed data , complexity in data integration and data access, and growing data compliance mandates. Animal, Vegetable, or Architecture?

Architecture 49

Architecture Data Government Agile 49

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 ). But the current data lakehouse architectural pattern is not enough.

Data 83

Data Analytics Machine Learning Artificial Inteligence 83

Altexsoft

JANUARY 14, 2021

We’ll review all the important aspects of their architecture, deployment, and performance so you can make an informed decision. Before jumping into the comparison of available products right away, it will be a good idea to get acquainted with the data warehousing basics first. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

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. Infrastructure.

Government 71

Government Artificial Inteligence Enterprise Strategy 71

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

Altexsoft

AUGUST 22, 2022

What’s more, Gartner identifies data fabric implementation as one of the top strategic technology trends for 2022 and expects that by 2024, data fabric deployments will increase the efficiency of data use while halving human-driven data management tasks. What is data fabric? Data fabric architecture example.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52

Altexsoft

JUNE 6, 2019

The use of ML-powered analytics solutions can help businesses forecast inventory demand with high accuracy. Systems that rely on machine learning are capable of analyzing a multitude of data points, finding subtle patterns (indicating changes in customer preferences, behavior, or satisfaction) which can be non-obvious for a human.

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

Mobilunity

NOVEMBER 24, 2021

The demand for specialists who know how to process and structure data is growing exponentially. 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. Who Is an ETL Engineer? Data modeling.

Development 52

Development Storage Recruiting Architecture 52

Altexsoft

MARCH 16, 2021

In general, a data infrastructure is a system of hardware and software tools used to collect, store, transfer, prepare, analyze, and visualize data. Check our article on data engineering to get a detailed understanding of the data pipeline and its components. Big data infrastructure in a nutshell.

Big Data 116

Big Data Healthcare Applications Data 116

Cloudera

DECEMBER 21, 2020

Instead, it is a move towards recognizing those companies that are driving innovation and agility by modernizing their data architecture and optimizing their infrastructure to leverage invaluable insights. This year’s winner, the West Midlands Police, stood out with its groundbreaking data strategy that did both of these things.

Data 92

Data Technical Review Cloud Enterprise 92

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

Altexsoft

MARCH 2, 2023

Data governance , on the other hand, focuses on the strategic and organizational aspects of managing data, such as establishing policies and procedures for data use and ensuring compliance with regulatory requirements. Compliance. Improved data management. sales specialists).

Government 52

Government Tools Data Weak Development Team 52