Xebia

DECEMBER 23, 2024

A lack of monitoring might result in idle clusters running longer than necessary, overly broad data queries consuming excessive compute resources, or unexpected storage costs due to unoptimized data retention. Once the decision is made, inefficiencies can be categorized into two primary areas: compute and storage.

Data 130

Data Storage Culture Resources 130

Netflix Tech

JUNE 20, 2024

A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024 The Data Engineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.

Data Engineering 82

Data Engineering Engineering Data Generative AI 82

Xebia

DECEMBER 23, 2024

A lack of monitoring might result in idle clusters running longer than necessary, overly broad data queries consuming excessive compute resources, or unexpected storage costs due to unoptimized data retention. Once the decision is made, inefficiencies can be categorized into two primary areas: compute and storage.

Data 130

Data Storage Culture Resources 130

Xebia

OCTOBER 18, 2024

However, DuckDB doesn’t provide data governance support yet. Unity Catalog gives you centralized governance, meaning you get great features like access controls and data lineage to keep your tables secure, findable and traceable. Dbt is a popular tool for transforming data in a data warehouse or data lake.

Open Source 162

Open Source AWS Government Technical Review 162

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

CIO

NOVEMBER 14, 2024

Recently, we sponsored a study with IDC* that surveyed teams of data scientists, data engineers, developers, and IT professionals working on AI projects across enterprises worldwide. Another significant finding was that respondents cited data access due to infrastructure restrictions as the #1 cause of AI project failure.

Enterprise 124

Enterprise Survey Storage Study 124

Cloudera

JANUARY 12, 2018

I mentioned in an earlier blog titled, “Staffing your big data team, ” that data engineers are critical to a successful data journey. That said, most companies that are early in their journey lack a dedicated engineering group. Image 1: Data Engineering Skillsets.

Data Engineering 54

Data Engineering Big Data Engineering Data 54

CIO

JUNE 19, 2024

They may also ensure consistency in terms of processes, architecture, security, and technical governance. Our platform engineering teams, which support more than 200 applications, have innovated around automation,” says Bob Simms, former director of enterprise infrastructure delivery at the US Patent and Trademark Office (USPTO).

Weak Development Team 208

Weak Development Team Engineering UI/UX Software Development 208

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. Using a single data context, well-governed, ensures we have the best quality data available to all users at once.

Cloud 111

Cloud Data Compliance Analytics 111

CIO

JULY 6, 2023

OCI’s Supercluster includes OCI Compute Bare Metal, which provides an ultralow-latency remote direct access memory (RDMA) over a Converged Ethernet (RoCE) cluster for low-latency networking, and a choice of high-performance computing storage options.

Generative AI 170

Generative AI Artificial Inteligence Strategy Google Cloud 170

InfoWorld

FEBRUARY 9, 2024

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. In many ways, Fabric is Microsoft’s answer to Google Cloud Dataplex. As of this writing, Fabric is in preview.

Big Data 78

Big Data Data Azure Google Cloud 78

CIO

AUGUST 2, 2023

The third and most complicated layer is architecture and governance, which we’ve linked together as one layer. The last layer is raw data, which is where we get the data out of the source systems, organize it, secure it, and figure out which data lakes to use. What happens at the architecture and governance layer?

Data 147

Data Architecture Government Strategy 147

CIO

FEBRUARY 14, 2023

Organizations have balanced competing needs to make more efficient data-driven decisions and to build the technical infrastructure to support that goal. Many companies today struggle with legacy software applications and complex environments, which leads to difficulty in integrating new data elements or services.

Artificial Inteligence 174

Artificial Inteligence Strategy Data Machine Learning 174

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 89

Cloud Government Analytics Storage 89

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

CIO

JUNE 14, 2023

CDP Generalist The Cloudera Data Platform (CDP) Generalist certification verifies proficiency with the Cloudera CDP platform. The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect.

Big Data 190

Big Data Analytics Data eLearning 190

CIO

JANUARY 19, 2024

The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. The exam consists of 60 questions and the candidate has 90 minutes to complete it.

Artificial Inteligence 190

Artificial Inteligence Data Machine Learning Azure 190

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 88

Trends Data Machine Learning Artificial Inteligence 88

Cloudera

OCTOBER 23, 2024

The Iceberg REST catalog specification is a key component for making Iceberg tables available and discoverable by many different tools and execution engines. It enables easy integration and interaction with Iceberg table metadata via an API and also decouples metadata management from the underlying storage.

Data 84

Data Analytics Systems Review Architecture 84

Altexsoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. What is the main difference between a data architect and a data engineer? By the way, we have a video dedicated to the data engineering working principles.

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

SEPTEMBER 29, 2020

A TPC-DS 10TB dataset was generated in ACID ORC format and stored on the ADLS Gen 2 cloud storage. Cloudera Data Warehouse vs HDInsight. Finally, CDW is offered in CDP along with other data lifecycle services – Data Engineering, Operational Database, Machine Learning, and Data Hub.

Azure 121

Azure Data Comparison Virtualization 121

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

Apiumhub

DECEMBER 9, 2024

Azure Key Vault Secrets offers a centralized and secure storage alternative for API keys, passwords, certificates, and other sensitive statistics. Azure Key Vault is a cloud service that provides secure storage and access to confidential information such as passwords, API keys, and connection strings. What is Azure Key Vault Secret?

Azure 89

Azure Analytics Storage Machine Learning 89

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 97

Data Scalability Storage Big Data 97

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

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 ). Why integrate Apache Iceberg with Cloudera Data Platform?

Data 88

Data Analytics Machine Learning Artificial Inteligence 88

Datavail

MARCH 10, 2022

There are many reasons for this failure, but poor (or a complete lack of) data governance strategies is most often to blame. This article discusses the importance of solid data governance implementation plans and why, despite its obvious benefits, many organizations find data governance implementation to be challenging.

Government 40

Government Strategy Weak Development Team Company 40

CIO

OCTOBER 16, 2024

One specific area is selecting and balancing multiple energy sources, like wind, solar, or battery storage, based on cost and forecasts, and automatically optimizing bidirectional power flow. Another sector is manufacturing.

Technical Advisors 215

Technical Advisors Energy Technical Review CTO Coach 215

Cloudera

AUGUST 30, 2022

Data is the fuel that drives government, enables transparency, and powers citizen services. Data quality issues deter trust and hinder accurate analytics. Citizens who have negative experiences with government services are less likely to use those services in the future. Modern data architectures.

Architecture 79

Architecture Data Artificial Inteligence Artificial Intelligence 79

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. What is Apache Iceberg? 1: Multi-function analytics .

Data 92

Data Open Source Storage Machine Learning 92

Cloudera

JANUARY 20, 2021

The data journey is not linear, but it is an infinite loop data lifecycle – initiating at the edge, weaving through a data platform, and resulting in business imperative insights applied to real business-critical problems that result in new data-led initiatives. Fig 1: The Enterprise Data Lifecycle.

Data 110

Data Artificial Inteligence Analytics Machine Learning 110

Cloudera

JANUARY 15, 2021

Optimized read and write paths to cloud object stores (S3, Azure Data Lake Storage, etc) with local caching, allowing workloads to run directly against data in shared object stores without explicit loading to local storage. No local data loading step was required prior to query execution.

Performance 97

Performance Cloud Data Storage 97

Cloudera

FEBRUARY 16, 2022

Model interpretability is one of five main components of model governance. In this article, we explore model governance, a function of ML Operations (MLOps). Each project consists of a declarative series of steps or operations that define the data science workflow. blueberry spacing) is a measure of the model’s interpretability.

Machine Learning 85

Machine Learning Artificial Inteligence Weak Development Team Construction 85

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. Regulated data also needs to show lineage, a history of where the data came from and what has been done with it.

Data 90

Data Artificial Inteligence Machine Learning Weak Development Team 90

Cloudera

FEBRUARY 22, 2022

Today, we are announcing a private technical preview (TP) release of Iceberg for CDP Data Services in the public cloud, including Cloudera Data Warehousing ( CDW ) and Cloudera Data Engineering ( CDE ). . That is why from day one we ensured the same security and governance of SDX apply to Iceberg tables.

Data 110

Data Analytics Travel Disaster Recovery 110

Cloudera

OCTOBER 7, 2022

We’re excited to announce the general availability of the open source adapters for dbt for all the engines in CDP — Apache Hive , Apache Impala , and Apache Spark, with added support for Apache Livy and Cloudera Data Engineering. Cloudera has built dbt adapters for all of the engines in the open data lakehouse.

SDLC 81

SDLC Data Open Source Handbook 81

TIBCO - Connected Intelligence

AUGUST 10, 2020

Taking action to leverage your data is a multi-step journey, outlined below: First, you have to recognize that sticking to the status quo is not an option. Your data demands, like your data itself, are outpacing your data engineering methods and teams.

Virtualization 69

Virtualization Data How To Data Engineering 69