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 This makes it easier to test intermediate results, simplifies code, and often produces simpler SQL code that runs faster.

Data Engineering 69

Data Engineering Engineering Data Storage 69

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Xebia

JANUARY 9, 2024

Yes, dbt does provide logs to the stdout for every model and test execution, however in my opinion this is not sufficient to base your whole monitoring around. These log records will show the name of the model or test, the execution time, and the execution status (passed, warned, or failed). Whenever dbt runs (e.g.

Testing 130

Testing Data Open Source Google Cloud 130

Altexsoft

OCTOBER 30, 2021

Engineers are not only the ones bearing helmets and operating on construction sites. Scientists don’t always wear lab coats or handle test tubes. Explaining the difference, especially when they both work with something intangible such as data , is difficult. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

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. What’s next.

Data Engineering 83

Data Engineering Performance Engineering Data 83

Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

Trigent

JUNE 20, 2022

To do this, they are constantly looking to partner with experts who can guide them on what to do with that data. This is where data engineering services providers come into play. Data engineering consulting is an inclusive term that encompasses multiple processes and business functions.

Data Engineering 52

Data Engineering Engineering Data Strategy 52

Gorilla Logic

APRIL 27, 2022

Are you a data engineer or seeking to become one? This is the first entry of a series of articles about skills you’ll need in your everyday life as a data engineer. This blog post is for you. So let’s begin with the first and, in my opinion, the most useful tool in your technical tool belt, SQL. CROSS JOIN.

Data Engineering 59

Data Engineering Engineering Data Windows 59

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Engineering 92

Data Engineering Engineering Data Cloud 92

Mobilunity

AUGUST 3, 2021

The cloud offers excellent scalability, while graph databases offer the ability to display incredible amounts of data in a way that makes analytics efficient and effective. Who is Big Data Engineer? Big Data requires a unique engineering approach. Big Data Engineer vs Data Scientist.

Big Data 52

Big Data Data Engineering Engineering Data 52

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. Candidates for the exam are tested on ML, AI solutions, NLP, computer vision, and predictive analytics.

Artificial Inteligence 315

Artificial Inteligence Data Machine Learning Azure 315

Altexsoft

OCTOBER 29, 2020

How do you trust data with any transformative decisions when there’s a chance that some of it has been lost, or incomplete, or is simply irrelevant to your business case? What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

The Crazy Programmer

NOVEMBER 6, 2021

A cloud architect has a profound understanding of storage, servers, analytics, and many more. They are responsible for designing, testing, and managing the software products of the systems. Big Data Engineer. Another highest-paying job skill in the IT sector is big data engineering. Software Architect.

Artificial Inteligence 290

Artificial Inteligence Blockchain Artificial Intelligence Software Review 290

CIO

JUNE 14, 2023

Organization: AWS Price: US$300 How to prepare: Amazon offers free exam guides, sample questions, practice tests, and digital training. CDP Data Analyst The Cloudera Data Platform (CDP) Data Analyst certification verifies the Cloudera skills and knowledge required for data analysts using CDP.

Big Data 315

Big Data Analytics Data eLearning 315

CIO

SEPTEMBER 2, 2022

The average salary for a financial software engineer is $116,670 per year, with a reported salary range of $85,000 to $177,000 per year, according to data from Glassdoor. Full-stack software engineer. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

AUGUST 31, 2022

The average salary for a financial software engineer is $116,670 per year, with a reported salary range of $85,000 to $177,000 per year, according to data from Glassdoor. Full-stack software engineer. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

Cloudera

NOVEMBER 28, 2023

It offers a fully featured open data lakehouse with services including data warehousing, machine learning, and data engineering, in hybrid and multi-cloud environments. This means you can expect simpler data management and drastically improved productivity for your business users.

Data 82

Data Scalability Analytics Quality Assurance 82

CIO

JUNE 7, 2022

Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. Data analytics and data science are closely related.

Analytics 332

Analytics Data Analysis Business Analytics 332

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 76

Tools Data Engineering Analytics Testing 76

Cloudera

FEBRUARY 12, 2024

In this blog, we’ll take you through our tried and tested best practices for setting up your DNS for use with Cloudera on Azure. In a Cloudera deployment scenario, only storage accounts, PostgreSQL DB, and Key Vault support service endpoints. There is at present no option to disable private DNS zones for data engineering.

Azure 52

Azure Firewall Data Engineering Storage 52

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

CIO

JUNE 22, 2023

There’s a high demand for software engineers, data engineers, business analysts and data scientists, as finance companies move to build in-house tools and services for customers.

Industry 300

Industry UI/UX Telecommunications Quality Assurance 300

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. Flexible and easy-to-work-with data models are the oil that makes the engine for building models run smoothly. The storage for these features is referred to as a feature store.

Artificial Inteligence 282

Artificial Inteligence Strategy Data Machine Learning 282

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Supports Disaggregation of compute and storage.

Data 100

Data Storage Architecture Big Data 100

Hu's Place - HitachiVantara

APRIL 11, 2019

Few if any data management frameworks are business focused, to not only promote efficient use of data and allocation of resources, but also to curate the data to understand the meaning of the data as well as the technologies that are applied to the data so that data engineers can move and transform the essential data that data consumers need.

Data Engineering 81

Data Engineering Machine Learning Artificial Inteligence Technical Review 81

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

Altexsoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Netflix Tech

FEBRUARY 9, 2022

Let’s define some requirements that we are interested in delivering to the Netflix data engineers or anyone who would like to schedule a workflow with some external assets in it. How do you set up your deployment logic to know when to deploy the workflow to a test or dev environment? Is a single location enough?

Data 80

Data Testing Software Review Systems Review 80

Kentik

APRIL 4, 2023

It takes cross-departmental planning to envision, create, test, and monitor the best-for-business version of a reliable network. However, arriving at specs for other aspects of network performance requires extensive monitoring, dashboarding, and data engineering to unify this data and help make it meaningful.

Network 104

Network Load Balancer Cloud Backup 104

Mobilunity

NOVEMBER 24, 2021

In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. In this article, we’ll discuss the role of an ETL engineer in data processing and why businesses need such experts nowadays. Who Is an ETL Engineer?

Development 52

Development Storage Recruiting Architecture 52

Cloudera

AUGUST 26, 2020

The Cloudera Connect Technology Certification program uses a well-documented process to test and certify our Independent Software Vendors’ (ISVs) integrations with our data platform. Informatica and Cloudera deliver a proven set of solutions for rapidly curating data into trusted information.

Data 82

Data Machine Learning Artificial Inteligence Disaster Recovery 82

Altexsoft

JULY 18, 2023

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Perficient

APRIL 1, 2024

Traditionally, organizations used to provision multiple services of Azure Services, like Azure Storage, Azure Databricks, etc. Postman: Postman is a popular tool mostly used for API testing (limited feature free edition available). Polygon.io: It is a market data platform offering API to query stock prices & related information.

Data 64

Data Azure Case Study Data Engineering 64

Cloudera

JULY 14, 2023

While these instructions are carried out for Cloudera Data Platform (CDP), Cloudera Data Engineering, and Cloudera Data Warehouse, one can extrapolate them easily to other services and other use cases as well. All you have to do is to alter the table properties to set the storage handler to “HiveIcebergStorageHandler.”

Backup 70

Backup Data Engineering Engineering Data 70

Erik Bernhardsson

DECEMBER 6, 2022

In backend development it's running unit tests (or sometimes, just compiling). Data is sort of weird because you have to run things on production data to have these sort of feedback loops. Whether you're running SQL or doing ML, it's often pointless to do that on non-production data. I will be posting a lot more about it!

CTO Coach 242

CTO Coach Fractional CTO Software Engineering Serverless 242

Cloudera

FEBRUARY 1, 2024

Day 1 — Deployment and Migration: Involves the actual deployment and initial configuration of the platform, including installation, configuration, testing, troubleshooting, and setting up monitoring tools, as well as migrating your data and workloads onto the platform. How does Cloudera support Day 2 operations?

Backup 82

Backup Architecture Cloud Resources 82

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