CIO

FEBRUARY 14, 2023

This has also accelerated the execution of edge computing solutions so compute and real-time decisioning can be closer to where the data is generated. AI continues to transform customer engagements and interactions with chatbots that use predictive analytics for real-time conversations. report they have established a data culture 26.5%

Artificial Inteligence 290

Artificial Inteligence Strategy Data Machine Learning 290

Cloudera

NOVEMBER 1, 2022

It’s no secret that IT modernization is a top priority for the US federal government. 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.

Cloud 90

Cloud Government Storage Analytics 90

Altexsoft

FEBRUARY 11, 2023

Data is now one of the most valuable assets for any kind of business. 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. Feel free to enjoy it. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

JULY 24, 2023

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

Open Source 68

Open Source Analytics Software Review Metrics 68

InnovationM

MAY 14, 2023

In this article, I will share practical insights and technologies utilized in building and harnessing the potential of data lakes. Demystifying Data Lakes Data lakes serve as flexible storage repositories, enabling organizations to store raw and diverse data types, breaking away from the constraints of traditional data warehouses.

Data 52

Data Storage Construction Business Intelligence 52

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

Kentik

APRIL 12, 2023

Data scientists play a critical role in the DataOps ecosystem, leveraging advanced analytics and machine learning techniques to gain insights from large and complex data sets. DataOps strategies require a robust data infrastructure, including data warehouses, data lakes, caches, and other data storage and processing systems.

Network 52

Network Data Engineering Machine Learning Artificial Inteligence 52

Mobilunity

MAY 8, 2023

Key zones of an Enterprise Data Lake Architecture typically include ingestion zone, storage zone, processing zone, analytics zone, and governance zone. Ingestion zone is where data is collected from various sources and ingested into the data lake. This includes data cleansing, normalization, and enrichment.

Engineering 52

Engineering Data Storage AWS 52

Hu's Place - HitachiVantara

APRIL 11, 2019

Few Data Management Frameworks are Business Focused Data management has been around since the beginning of IT, and a lot of technology has been focused on big data deployments, governance, best practices, tools, etc. However, large data hubs over the last 25 years (e.g.,

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

O'Reilly Media - Ideas

JANUARY 8, 2019

The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. LinkedIn recently found that demand for data scientists in the US is “off the charts,” and our survey indicated that the demand for data scientists and data engineers is strong not just in the US but globally.

Trends 89

Trends Data Machine Learning Artificial Inteligence 89

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Data 110

Data Artificial Inteligence Analytics Machine Learning 110

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. Metadata storage. Types of metadata. Source: Pagefreezer.

Tools 59

Tools Technical Review Software Review Systems Review 59

Cloudera

SEPTEMBER 29, 2020

CDW is an analytic offering for Cloudera Data Platform (CDP). On CDW, when you provision a Virtual Warehouse against your Data Catalog (catalog of table and views), the platform provides fully tuned LLAP worker nodes ready to run your queries. Cloudera Data Warehouse vs HDInsight. Benchmark Configuration.

Azure 120

Azure Data Comparison Virtualization 120

Cloudera

JULY 27, 2021

Data has become the critical fuel that drives growth and automation, the twin guide points for an industry stretching for new revenue sources and cost reduction, all the while maintaining governance on precious customer data. Edge analytics by definition require in-network deployment.

Telecommunications 62

Telecommunications Data Architecture Big Data 62

Hu's Place - HitachiVantara

MAY 10, 2019

For this reason, many financial institutions are converting their fraud detection systems to machine learning and advanced analytics and letting the data detect fraudulent activity. However, in the rush to do this, many of these systems have been poorly architected to address the total analytics pipeline.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

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

Cloudera

JANUARY 15, 2021

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. As depicted in the chart, Cloudera Data Warehouse ran the benchmark with significantly better price-performance than any of the other competitors tested. Introduction.

Performance 97

Performance Cloud Data Storage 97

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 85

Data Analytics Cloud Technical Review 85

Existek

JANUARY 11, 2022

The cloud computing market covers many areas like business processes, infrastructure, platform, security, management, analytics supported by cloud providers. Governments . Governments. In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2. Data and analytics.

Azure 52

Azure AWS Cloud How To 52

Cloudera

NOVEMBER 6, 2017

While cloud services do provide useful resources — such as compute instances and object storage on demand — Cloudera offers the unified platform to organize, process, analyze, and store data at large scale… anywhere. As cloud vendors continue to compete with ever lower costs, data and analytics remain portable.

Cloud 40

Cloud Azure Analytics AWS 40

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Hybrid clouds must bond together the two clouds through fundamental technology, which will enable the transfer of data and applications. Public cloud also introduces new challenges in governance, financial management and integration. Engagements may be on a short-term tactical basis or as part of a long-term managed service.

Cloud 78

Cloud Google Cloud Azure AWS 78

TIBCO - Connected Intelligence

DECEMBER 11, 2020

Like the rest of the world, data is transforming the landscape of how Nordics citizens live and work, how commerce occurs, how its governments engage, and so much more. Over time, as TIBCO added analytics capabilities and a broad set of data management solutions, we also added these to our solution mix.”.

Business Transformation 52

Business Transformation Data Analytics Hotels 52

AWS Machine Learning - AI

JANUARY 26, 2024

Consider your security posture, governance, and operational excellence when assessing overall readiness to develop generative AI with LLMs and your organizational resiliency to any potential impacts. AWS is architected to be the most secure global cloud infrastructure on which to build, migrate, and manage applications and workloads.

Artificial Inteligence 119

Artificial Inteligence Generative AI Security Applications 119

TIBCO - Connected Intelligence

MARCH 5, 2020

Over the past sixty years, technology has redefined how people live and work, how commerce occurs, how citizens and governments engage, and so much more. 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.

Technology 42

Technology Games Trends IoT 42

KitelyTech

FEBRUARY 3, 2021

Database management is what your database administrator uses to store, organize, and access computer data. It often includes three main components like the database schema, database application, and data engine. Database management systems must be flexible enough to handle large amounts of data in a short period of time.

Big Data 52

Big Data Data Development Business Intelligence 52

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. This greatly increases data processing capabilities.

Big Data 75

Big Data Data Engineering Engineering Data 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

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

SEPTEMBER 17, 2020

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. CDP data lifecycle integration and SDX security and governance.

Data Engineering 104

Data Engineering Engineering Data Tools 104

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

InfoWorld

FEBRUARY 9, 2024

Microsoft Fabric is an end-to-end, software-as-a-service (SaaS) platform for data analytics. It is built around a data lake called OneLake, and brings together new and existing components from Microsoft Power BI, Azure Synapse, and Azure Data Factory into a single integrated environment.

Big Data 87

Big Data Azure Google Cloud Data 87

Kentik

APRIL 11, 2016

Clustered computing for real-time Big Data analytics. It has since gone on to become a key technology for running many web-scale services and products, and has also landed in traditional enterprise and government IT organizations for solving big data problems in finance, demographics, intelligence, and more.

Big Data 40

Big Data Analytics Network Architecture 40

Datavail

JUNE 15, 2023

The Microsoft Fabric announcement at Microsoft Build 2023 has caused quite a stir in the data and analytics world. Microsoft Fabric is an all-in-one analytics solution that brings together seven Azure services on a shared SaaS foundation, in a unified experience combined with AI.

Azure 52

Azure Analytics Storage Generative AI 52

CIO

JUNE 14, 2023

Start with storage. Before you can even think about analyzing exabytes worth of data, ensure you have the infrastructure to store more than 1000 petabytes! Going from 250 PB to even a single exabyte means multiplying storage capabilities four times. Merely adding more data nodes is insufficient. Focus on scalability.

Data 162

Data Scalability Storage Big Data 162

Datavail

MARCH 10, 2022

According to Gartner, only 20 percent of analytics insights will deliver business results through 2022. In other words, 80 percent of companies’ Big Data projects will fail and/or not deliver results. There are many reasons for this failure, but poor (or a complete lack of) data governance strategies is most often to blame.

Government 40

Government Strategy Weak Development Team Company 40

Cloudera

APRIL 26, 2023

At its core, CDP Private Cloud Data Services (“the platform”) is an end-to-end cloud native platform that provides a private open data lakehouse. It offers features such as data ingestion, storage, ETL, BI and analytics, observability, and AI model development and deployment.

Cloud 65

Cloud Data Load Balancer Storage 65

Cloudera

MARCH 23, 2022

Please join us on March 24 for Future of Data meetup where we do a deep dive into Iceberg with CDP . Apache Iceberg is a high-performance, open table format, born-in-the cloud that scales to petabytes independent of the underlying storage layer and the access engine layer. 1: Multi-function analytics .

Data 93

Data Open Source Storage Machine Learning 93