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

Cloudera

SEPTEMBER 2, 2021

The shift to cloud has been accelerating, and with it, a push to modernize data pipelines that fuel key applications. At Cloudera, we introduced Cloudera Data Engineering (CDE) as part of our Enterprise Data Cloud product — Cloudera Data Platform (CDP) — to meet these challenges. fixed sized clusters).

Data Engineering 85

Data Engineering Performance Engineering Data 85

CIO

JULY 28, 2022

For the past few years, IT leaders at a US financial services company have been struggling to hire data scientists to harness the increasing flood of incoming data that, if used properly, could improve customer experience and drive new products. It’s exponentially harder when it comes to data scientists.

Data 359

Data Machine Learning Artificial Inteligence Fractional CTO 359

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

JANUARY 19, 2024

Data scientist is one of the hottest jobs in IT. Companies are increasingly eager to hire data professionals who can make sense of the wide array of data the business collects. According to data from PayScale, $99,842 is the average base salary for a data scientist in 2024.

Artificial Inteligence 317

Artificial Inteligence Data Machine Learning Azure 317

The Programmer's Paradox

OCTOBER 14, 2022

The foundation of all software systems is persistent data. Building on top of broken foundations is a waste of time and resources. If it takes a few minutes to get to infrequent data, that is fine. If you just collect data blindly, the quality of that data will always be very poor. All of them.

Data Engineering 40

Data Engineering Engineering Data Software Review 40

Dzone - DevOps

MAY 31, 2023

In this detailed and personal account, the author shared his journey of building and evolving data pipelines in the rapidly transforming streaming media industry. In the last two decades, data engineering has dramatically transformed industries.

Data Engineering 52

Data Engineering Media Industry Engineering 52

Cloudera

AUGUST 20, 2020

Data from the US Treasury website show which companies received PPP loans and how many jobs were retained. Analysis of this data presents three challenges. First, the size of the data is significant. The amount of time to pull, curate, transform, retrieve and report on that data is time intensive. Objective.

Data Engineering 65

Data Engineering Engineering Programming Data 65

Cloudera

APRIL 30, 2021

Cloudera Data Engineering (CDE) is a cloud-native service purpose-built for enterprise data engineering teams. CDE’s APIs automatically generate the required resource behind the scenes, and mount the files to all the Spark pods at /app/mount path. . Create a resource for the application file.

Data Engineering 65

Data Engineering Engineering Data Software Review 65

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

TechCrunch

JANUARY 10, 2023

The need for data observability, or the ability to understand, diagnose and orchestrate data health across various IT tools, continues to grow as organizations adopt more apps and services. Other observability vendors with substantial backing behind them include Manta , Observe , Better Stack , Coralogix and Unravel Data.

Data 241

Data Software Review Technical Review Systems Review 241

Cloudera

OCTOBER 19, 2021

Airflow has been adopted by many Cloudera Data Platform (CDP) customers in the public cloud as the next generation orchestration service to setup and operationalize complex data pipelines. Multiple steps comprise the overall pipeline, which are stored as pipeline definition files in the CDE resource of the job.

Data Engineering 120

Data Engineering Engineering Data Virtualization 120

CIO

JULY 10, 2023

For a decade, Edmunds, an online resource for automotive inventory and information, has been struggling to consolidate its data infrastructure. Now, with the infrastructure side of its data house in order, the California-based company is envisioning a bold new future with AI and machine learning (ML) at its core.

Infrastructure 246

Infrastructure Artificial Inteligence Data Generative AI 246

TechCrunch

MAY 26, 2022

Over the last decade, the rate at which organizations create data has accelerated as it becomes cheaper to store, access, and process data. But as data continues to grow in scale and complexity, it’s becoming scattered across apps and platforms — often leading to problems where it concerns data quality.

Data 228

Data Weak Development Team Enterprise Analysis 228

TechCrunch

AUGUST 8, 2022

In a recent MuleSoft survey , 84% of organizations said that data and app integration challenges were hindering their digital transformations and, by extension, their adoption of cloud platforms. Systems, an IT consulting firm focused on data analytics. Prior to co-founding Equalum, Livneh was a full stack developer in the U.S.

Company 191

Company Data Google Cloud Cloud 191

TechBeacon

MAY 13, 2022

Account for growth, being fully aware that as the application nears production, usage and resource allocation will scale. DevOps teams know the drill: Create an environment, prepare the infrastructure, and align the elements for performance. Perhaps someone even sharded databases so there's wiggle room for expansion.

Data Engineering 52

Data Engineering Engineering Data DevOps 52

TechCrunch

DECEMBER 9, 2020

that was building what it dubbed an “operating system” for data warehouses, has been quietly acquired by Google’s Google Cloud division. Dataform scores $2M to build an ‘operating system’ for data warehouses. Dataform, a startup in the U.K.

Google Cloud 242

Google Cloud Data Operating System Business Intelligence 242

CIO

APRIL 10, 2024

Inferencing crunches millions or even billions of data points, requiring a lot of computational horsepower. As with many data-hungry workloads, the instinct is to offload LLM applications into a public cloud, whose strengths include speedy time-to-market and scalability. Inferencing and… Sherlock Holmes???

Artificial Inteligence 338

Artificial Inteligence Generative AI Storage Artificial Intelligence 338

TechCrunch

OCTOBER 7, 2021

Increasingly, conversations about big data, machine learning and artificial intelligence are going hand-in-hand with conversations about privacy and data protection. They could see that the longer-term issue would be a growing need and priority for data privacy. “But now we are running into the bottleneck of the data. .

Artificial Inteligence 246

Artificial Inteligence Technical Review Engineering Data 246

Dzone - DevOps

JUNE 4, 2024

In the evolving landscape of data engineering, reverse ETL has emerged as a pivotal process for businesses aiming to leverage their data warehouses and other data platforms beyond traditional analytics. Reverse ETL can be visualized as a cycle that begins with data aggregated in a data warehouse.

Operating System 84

Operating System Analytics Data Engineering Resources 84

ParkMyCloud

DECEMBER 11, 2020

If you’re looking to break into the cloud computing space, or just continue growing your skills and knowledge, there are an abundance of resources out there to help you get started, including free Google Cloud training. You’ll find several Google Cloud resources to help level up your skills. Google Cloud Free Program. Plural Sight.

Google Cloud 97

Google Cloud Training Resources Cloud 97

Kentik

FEBRUARY 27, 2023

It means seeing trends and patterns from a macro level, but it also means getting very granular to pursue any line of analysis of your data. Still, it will be useless if it takes forever to do anything meaningful with that data. So how can we faster process the data in such a massive database?

Network 98

Network Data WAN Metrics 98

Xebia

MAY 31, 2022

Most of the online resources suggest to use Azure Data factory (ADF ) in Git mode instead of Live mode as it has some advantages. For example, ability to work on the resources as a team in a collaborative manner or ability to revert changes that introduced bugs. This implies that the Terraform code is stored in the Git repo.

Data Engineering 130

Data Engineering Azure Resources Engineering 130

CIO

JANUARY 17, 2023

Building and managing infrastructure yourself gives you more control — but the effort to keep it all under control can take resources away from innovation in other areas. Recording all those interactions generates a prodigious amount of data, but that’s not the half of it.

Data Engineering 314

Data Engineering Engineering Data CTO Coach 314

O'Reilly Media - Data

APRIL 11, 2018

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.

Data Engineering 280

Data Engineering Engineering Data Artificial Inteligence 280

Xebia

MARCH 10, 2021

Many organisations have a new ambition to become a data-driven organisation. In essence, this means the organisation wants to make better business decisions based on insights provided by data [4]. Data itself is not able to advise a business for better decision-making. Data & Analytics as a separate business domain.

DevOps 130

DevOps Data Analytics Policies 130

TechCrunch

JULY 12, 2022

Machine learning can provide companies with a competitive advantage by using the data they’re collecting — for example, purchasing patterns — to generate predictions that power revenue-generating products (e.g. At a high level, Tecton automates the process of building features using real-time data sources.

Artificial Inteligence 249

Artificial Inteligence Machine Learning Marketing Data Engineering 249

CIO

APRIL 12, 2023

By George Trujillo, Principal Data Strategist, DataStax I recently had a conversation with a senior executive who had just landed at a new organization. He had been trying to gather new data insights but was frustrated at how long it was taking. Real-time AI involves processing data for making decisions within a given time frame.

Artificial Inteligence 363

Artificial Inteligence Artificial Intelligence Machine Learning Agile 363

Cloudera

DECEMBER 21, 2020

In this blog we will take you through a persona-based data adventure, with short demos attached, to show you the A-Z data worker workflow expedited and made easier through self-service, seamless integration, and cloud-native technologies. In our data adventure we assume the following: . Company data exists in the data lake.

Data 97

Data Virtualization Banking Data Engineering 97

Cloudera

APRIL 9, 2021

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection.

Machine Learning 98

Machine Learning Artificial Inteligence Data Data Engineering 98

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

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 142

Machine Learning Artificial Inteligence Data Marketing 142

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

ChatGPT 64

ChatGPT Education Data Comparison 64

CIO

SEPTEMBER 18, 2023

There’s a lot of coordination and cleanup of data, workflow, and, with some customers, circuits,” he says. IDC analyst Jason Leigh says Verizon made the right move to build a tool to facilitate customer migrations, but adds that there will be challenges whenever a CIO or C-suite move their data and traffic to new environments.

Telecommunications 278

Telecommunications Network Systems Review Software Review 278

Xebia

MAY 16, 2023

Data Engineers were tempted by the pressure of the moment to give up on testing all together. There was no need for generating your own data; just take a percentage of production data. In many cases, these tasks ended up on the shoulders of the Data Engineers themselves. Overly restrictive governance.

Testing 130

Testing How To Data Engineering Engineering 130

CIO

APRIL 27, 2023

For technologists with the right skills and expertise, the demand for talent remains and businesses continue to invest in technical skills such as data analytics, security, and cloud. The demand for specialized skills has boosted salaries in cybersecurity, data, engineering, development, and program management. as of January.

Technical Review 290

Technical Review Software Review Systems Review Software Engineering 290

Netflix Tech

MARCH 4, 2024

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. the monetary costs of running the job) to avoid blindly recommending configurations with excessive resource consumption.

Machine Learning 84

Machine Learning Artificial Inteligence Data Systems Review 84