Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. Data pipelines are composed of multiple steps with dependencies and triggers. Securing and scaling storage.

Data Engineering 119

Data Engineering Technical Review Software Review Engineering 119

Perficient

FEBRUARY 13, 2023

Introduction: We often end up creating a problem while working on data. So, here are few best practices for data engineering using snowflake: 1.Transform Using COPY and SNOWPIPE is the fastest and cheapest way to load data. Especially important is the ability to reload and reprocess the data in the event of an error.

Data Engineering 69

Data Engineering Engineering Data Storage 69

Netflix Tech

OCTOBER 28, 2021

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.

Data Engineering 69

Data Engineering Engineering Data Software Engineering 69

Trigent

JUNE 20, 2022

Businesses worldwide are realizing the importance of the considerable volume of data they possess and the need to extract value from it and incorporate it into enhancing Customer Experience or simplifying operational processes for improved results. This is where data engineering services providers come into play.

Data Engineering 52

Data Engineering Engineering Data Strategy 52

CIO

FEBRUARY 14, 2023

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making.

Artificial Inteligence 290

Artificial Inteligence Strategy Data Machine Learning 290

Cloudera

SEPTEMBER 2, 2021

The shift to cloud has been accelerating, and with it, a push to modernize data pipelines that fuel key applications. That is why cloud native solutions which take advantage of the capabilities such as disaggregated storage & compute, elasticity, and containerization are more paramount than ever. fixed sized clusters).

Data Engineering 85

Data Engineering Performance Engineering Data 85

Cloudera

DECEMBER 20, 2022

Efficient use of data will therefore be critical to improving the competitiveness and productivity of assets, both traditional and renewable generation. Data efficiency in renewables. Effective use of data can have a direct impact on the cash flow of wind and solar generation companies in areas such as real-time decision making.

Energy 83

Energy Analytics Data Machine Learning 83

Mobilunity

AUGUST 3, 2021

Big Data is a collection of data that is large in volume but still growing exponentially over time. It is so large in size and complexity that no traditional data management tools can store or manage it effectively. While Big Data has come far, its use is still growing and being explored. Who is Big Data Engineer?

Big Data 52

Big Data Data Engineering Engineering Data 52

CIO

AUGUST 2, 2023

A data and analytics capability cannot emerge from an IT or business strategy alone. With both technology and business organization deeply involved in the what, why, and how of data, companies need to create cross-functional data teams to get the most out of it. How do they bring all of that data together?

Data 246

Data Architecture Government Strategy 246

CIO

SEPTEMBER 2, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work. Software engineer. Full-stack software engineer. Back-end software engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

AUGUST 31, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work. Software engineer. Full-stack software engineer. Back-end software engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

InfoWorld

MARCH 8, 2024

LinkedIn has decided to open source its data management tool, OpenHouse, which it says can help data engineers and related data infrastructure teams in an enterprise to reduce their product engineering effort and decrease the time required to deploy products or applications.

Open Source 74

Open Source Tools Data Engineering Storage 74

TechCrunch

MAY 18, 2022

Heartex, a startup that bills itself as an “open source” platform for data labeling, today announced that it landed $25 million in a Series A funding round led by Redpoint Ventures. We agreed that the only viable solution was to have internal teams with domain expertise be responsible for annotating and curating training data.

Open Source 203

Open Source Weak Development Team Artificial Inteligence Data 203

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. What is a data architect?

Data 87

Data Data Engineering Big Data Architecture 87

CIO

FEBRUARY 13, 2023

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). Cold: On-prem infrastructure As they did in 2022, many IT leaders are reducing investments in data centers and on-prem technologies. “We

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Mobilunity

MAY 8, 2023

An Enterprise Data Lake is a large, centralized repository that stores structured and unstructured data at scale. It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise.

Engineering 52

Engineering Data Storage AWS 52

InnovationM

MAY 14, 2023

Introduction As someone who has hands-on experience in constructing and leveraging data lakes, I can attest to the transformative power these repositories hold for organizations grappling with vast amounts of data. These systems ensure high availability and facilitate the storage of massive data volumes.

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

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. On data warehouses and data lakes. Iterations of the lakehouse.

Data 93

Data Analytics Open Source Architecture 93

The Crazy Programmer

NOVEMBER 6, 2021

Data Scientist. Data scientist is the most demanding profession in the IT industry. Currently, the demand for data scientists has increased 344% compared to 2013. hence, if you want to interpret and analyze big data using a fundamental understanding of machine learning and data structure. Big Data Engineer.

Artificial Inteligence 290

Artificial Inteligence Artificial Intelligence Blockchain Software Review 290

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data 84

Data Analytics Cloud Technical Review 84

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse. These costs impede the adoption of cloud-native data warehouses.

Data 98

Data Technical Review Storage Systems Review 98

Cloudera

NOVEMBER 16, 2022

Overall, it struck me that while data science is not new, most firms are still defining the mission of the data office and data officer. It’s clear firms seek to leverage data and embrace its potential insights, but most are forging ahead in largely uncharted territory.

Data 81

Data Insurance Metrics eBook 81

TechCrunch

APRIL 12, 2022

While companies find AI’s predictive power alluring, particularly on the data analytics side of the organization, achieving meaningful results with AI often proves to be a challenge. That’s where Flyte comes in — a platform for programming and processing concurrent AI and data analytics workflows.

Artificial Inteligence 202

Artificial Inteligence Machine Learning Open Source Biotech 202

Dzone - DevOps

FEBRUARY 16, 2023

The world is getting more and more value out of data, as exemplified by the currently much-talked-about ChatGPT, which I believe is a robotic data analyst. However, in today's era, what's more, important than the data itself is the ability to locate your wanted information among all the overflowing data quickly.

Data 71

Data ChatGPT Storage Architecture 71

O'Reilly Media - Data

JULY 18, 2018

While models and algorithms garner most of the media coverage, this is a great time to be thinking about building tools in data. In this post I share slides and notes from a keynote I gave at the Strata Data Conference in London at the end of May. Economic value of data.

Machine Learning 137

Machine Learning Artificial Inteligence Data Marketing 137

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. For data engineering and data science teams, CDSW is highly effective as a comprehensive platform that trains, develops, and deploys machine learning models.

Tools 78

Tools Data Engineering Analytics Testing 78

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. I will deep dive into the details and answer many questions about data integration.

Infrastructure 52

Infrastructure Cloud Data Linux 52

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 67

Open Source Analytics Software Review Metrics 67

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 120

Azure Data Comparison Virtualization 120

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. The results demonstrate superior price performance of Cloudera Data Warehouse on the full set of 99 queries from the TPC-DS benchmark. Introduction. higher cost.

Performance 96

Performance Cloud Data Storage 96

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 109

Data Artificial Inteligence Analytics Machine Learning 109

O'Reilly Media - Ideas

JANUARY 8, 2019

From infrastructure to tools to training, Ben Lorica looks at what’s ahead for data. Whether you’re a business leader or a practitioner, here are key data trends to watch and explore in the months ahead. Increasing focus on building data culture, organization, and training. Cloud for data infrastructure.

Trends 89

Trends Data Machine Learning Artificial Inteligence 89

Hu's Place - HitachiVantara

MAY 10, 2019

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. DataOps is required to engineer and prepare the data so that the machine learning algorithms can be efficient and effective.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

Cloudera

NOVEMBER 1, 2022

These systems also pose security risks, including the inability to use current security best practices, such as data encryption and multi-factor authentication, making these systems particularly vulnerable to malicious cyber activity. These are challenges that must be assessed and mitigated and ultimately resolved with data. .

Cloud 89

Cloud Government Storage Analytics 89

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. When it comes to Data and AI, the industry is increasingly committed to a hybrid cloud approach.

Telecommunications 62

Telecommunications Data Architecture Big Data 62

Kentik

APRIL 12, 2023

With modern networks’ increasing complexity and scale, it has become essential to collect and analyze data from various sources to gain insights into network performance, security, and availability. DataOps team roles In a DataOps team, several key roles work together to ensure the data pipeline is efficient, reliable, and scalable.

Network 52

Network Data Engineering Machine Learning Artificial Inteligence 52