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 65

Open Source Analytics Software Review Metrics 65

Cloudera

JUNE 26, 2023

Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster. It can provide a complete solution for data exploration, data analysis, data visualization, viz applications, and model deployment at scale.

Tools 75

Tools Data Engineering Analytics Testing 75

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.

Data 87

Data Data Engineering Big Data Architecture 87

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

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 post When Private Cloud is the Right Fit for Public Sector Missions appeared first on Cloudera Blog.

Cloud 84

Cloud Government Storage Analytics 84

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. Storage zone is where the raw data is stored in its original format.

Engineering 52

Engineering Data Storage AWS 52

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 92

Performance Cloud Data Storage 92

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. Data lakes and data warehouses unify large volumes and varieties of data into a central location.

Data 90

Data Analytics Open Source Architecture 90

Apps Associates

JULY 28, 2022

This blog introduces you to Oracle Cloud Infrastructure (OCI) Data Integration service and reviews how to setup Data Integration workspace in OCI. I love Data Integration in OCI and hope to get you excited about this great product as well. Use Case 2: Data integration for data marts and data warehousing.

Infrastructure 52

Infrastructure Cloud Data Linux 52

Cloudera

SEPTEMBER 29, 2020

Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. . Cloudera Data Warehouse vs HDInsight.

Azure 116

Azure Data Comparison Virtualization 116

Cloudera

NOVEMBER 16, 2022

A common theme that was highlighted continuously was using “storytelling” to relay the value that data and analytics teams bring to the business. This leads to a further challenge of the chief data and analytics officer’s role: Is the mission to play offense — drive revenue? Are you playing offense or defense?

Data 78

Data Insurance Metrics eBook 78

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 105

Data Artificial Inteligence Analytics Machine Learning 105

Cloudera

JULY 27, 2021

Considering the stack – as we say in Cloudera, from Edge to AI – there are certain elements particularly in ingestion, cleansing and data engineering, as well as in storage and warehousing, that lend themselves to on-premise deployments, either for networking, cost or regulatory reasons.

Telecommunications 61

Telecommunications Data Architecture Big Data 61

Confluent

FEBRUARY 6, 2019

It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. Impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

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

Cloudera

JULY 14, 2023

Depending on the size and usage patterns of the data, several different strategies could be pursued to achieve a successful migration. In this blog, I will describe a few strategies one could undertake for various use cases. This will be discussed in a later blog. Relatively fast as the underlying data files are kept in place.

Backup 69

Backup Data Engineering Engineering Data 69

Cloudera

JANUARY 6, 2021

Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle.

Machine Learning 132

Machine Learning Artificial Inteligence Data Applications 132

Cloudera

SEPTEMBER 1, 2020

DDE is a new template flavor within CDP Data Hub in Cloudera’s public cloud deployment option (CDP PC). It is designed to simplify deployment, configuration, and serviceability of Solr-based analytics applications. data best served through Apache Solr). data best served through Apache Solr). What does DDE entail?

Data 67

Data Backup Disaster Recovery Storage 67

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

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

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

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. This April, 47Lining, announced its Amazon Web Services (AWS) Industrial Time Series Data Connector Quick Start. We are all thrilled to welcome them to our own team of talented professionals.

Cloud 78

Cloud Google Cloud Azure AWS 78

TIBCO - Connected Intelligence

APRIL 22, 2021

Does that figure seem excessive, especially when more copies mean more storage, which requires servers that consume yet more power? Granted, you need backups, but even if you back up all your new data twice, you still consume 50% more energy to store all the other extra copies. Some analytic tools query data efficiently.

Sustainability 46

Sustainability Virtualization Data Energy 46

Altexsoft

AUGUST 19, 2022

In our blog, we’ve been talking a lot about the importance of business intelligence (BI), data analytics, and data-driven culture for any company. Multiple studies continuously demonstrate the superiority of analytics-based organizations (e.g., You get 10GB of cloud storage and can upload 1GB of data at a time.

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Kentik

JULY 18, 2016

Like the pre-dig Irwin family, surrounded by buried riches, too many network organizations are separated from the true value of their network data by legacy limitations on the collection, storage, and analysis of flow records (e.g. NetFlow) and other other network traffic data like BGP and GeoIP.

Big Data 40

Big Data Network Analytics Data 40

TIBCO - Connected Intelligence

DECEMBER 11, 2020

Over time, as TIBCO added analytics capabilities and a broad set of data management solutions, we also added these to our solution mix.”. That should give Enfo an excellent vantage point on the kinds of data-driven transformation underway. It seems data is a key enabler. But data can be troublesome.

Business Transformation 52

Business Transformation Data Analytics Hotels 52

TIBCO - Connected Intelligence

MARCH 5, 2020

To help you answer these questions, in part one of this blog series I contrasted technology predictions (less than sure projections of the future) so prevalent at this time of year, versus sure technology bets (those things you can be 100% sure will happen). Data Is The Wisest Bet for 2020. And how do you raise your odds of success?

Technology 42

Technology Games Trends IoT 42

ParkMyCloud

JULY 30, 2019

These are in fact Databricks being used to undertake data analytics workloads. Apache Spark is described as a unified analytics engine for large-scale data processing. To do this, Databricks offers a range of tools for building, managing and monitoring data pipelines.

Azure 40

Azure AWS Analytics Machine Learning 40

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

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. Enterprise Data Engineering From the Ground Up. Figure 1: Key component within CDP Data Engineering.

Data Engineering 102

Data Engineering Engineering Data Tools 102

Cloudera

NOVEMBER 28, 2023

With its rise in popularity generative AI has emerged as a top CEO priority, and the importance of performant, seamless, and secure data management and analytics solutions to power those AI applications is essential. This means you can expect simpler data management and drastically improved productivity for your business users.

Data 79

Data Scalability Analytics Quality Assurance 79

AWS Machine Learning - AI

JANUARY 26, 2024

Next, make sure that all data at rest is encrypted with AWS KMS, including considering the use of CMKs, and all data and models are versioned and backed up using Amazon Simple Storage Service (Amazon S3) versioning and applying object-level immutability with Amazon S3 Object Lock.

Artificial Inteligence 120

Artificial Inteligence Generative AI Security Applications 120

Perficient

FEBRUARY 16, 2024

In this blog post, we’ll explore into what DBFS is, how it works, and provide examples to illustrate its usage. DBFS is a distributed file system that comes integrated with Databricks, a unified analytics platform designed to simplify big data processing and machine learning tasks. What is DBFS? How does DBFS work?

System 52

System Storage Azure Big Data 52

Altexsoft

MARCH 31, 2020

It means you must collect transactional data and move it from the database that supports transactions to another system that can handle large volumes of data. And, as is common, to transform it before loading to another storage system. But how do you move data? The simplest illustration for a data pipeline.

Data 76

Data Storage Analytics Data Center 76

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 88

Data Open Source Storage Machine Learning 88

Cloudera

JULY 11, 2023

Apache Impala and Apache Kudu make a great combination for real-time analytics on streaming data for time series and real-time data warehousing use cases. In this blog we will explain how to integrate them together to achieve separation of compute (i.e. Impala) and storage (i.e.

Data 69

Data Virtualization Pharmaceuticals Storage 69

Cloudera

APRIL 26, 2023

Application modernization initiatives have led to cloud native architectures gaining popularity on premises, making it a sensible choice to extend to your data platform. 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.

Cloud 63

Cloud Data Load Balancer Storage 63