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. Securing and scaling storage. CDP Airflow Operators.

Data Engineering 117

Data Engineering Technical Review Software Review Engineering 117

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

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 71

Data Engineering Engineering Data Software Engineering 71

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 So, resist the temptation to periodically load data using other methods (such as querying external tables). Use it, but don’t use it for normal large data loads.

Data Engineering 69

Data Engineering Engineering Data Storage 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

Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

Altexsoft

APRIL 22, 2020

But, understanding and interpreting data is just a final stage in a long way, as the information goes from its raw format to the fancy analytical boards. So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

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 104

Data Engineering Engineering Data Tools 104

TechCrunch

NOVEMBER 4, 2022

I know this because I used to be a data engineer and built extract-transform-load (ETL) data pipelines for this type of offer optimization. Part of my job involved unpacking encrypted data feeds, removing rows or columns that had missing data, and mapping the fields to our internal data models.

Data 218

Data Storage Analytics Data Engineering 218

Mobilunity

AUGUST 3, 2021

Technologies that have expanded Big Data possibilities even further are cloud computing and graph databases. 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 52

Big Data Data Engineering Engineering Data 52

Altexsoft

APRIL 16, 2021

Later, this data can be: modified to maintain the relevance of what was stored, used by business applications to perform its functions, for example check product availability, etc. used for analytical purposes to understand how our business is running. So, we need a solution that’s capable of representing data from multiple dimensions.

Analytics 98

Analytics Analysis Storage Business Intelligence 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.

Data Engineering 84

Data Engineering Performance Engineering Data 84

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

JANUARY 19, 2024

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Not finding what you’re looking for?

Artificial Inteligence 317

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Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

Data 83

Data Analytics Systems Review Architecture 83

Xebia

OCTOBER 18, 2024

DuckDB is an in-process analytical database designed for fast query execution, especially suited for analytics workloads. However, DuckDB doesn’t provide data governance support yet. Dbt is a popular tool for transforming data in a data warehouse or data lake. Why Integrate DuckDB with Unity Catalog?

Open Source 162

Open Source AWS Government Technical Review 162

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 162

Data Scalability Storage Big Data 162

InfoWorld

FEBRUARY 9, 2024

Microsoft Fabric is an end-to-end, software-as-a-service (SaaS) platform for data analytics. 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.

Big Data 78

Big Data Azure Data Google Cloud 78

Cloudera

DECEMBER 20, 2022

In this respect, several studies project that a proper use of advanced analytics implies savings of between 5% and 7.5%. The impact of the use of different analytical techniques in this field increases the profitability of these companies by 5% to 10%, at the same time increasing the brand value by increasing customer satisfaction.

Energy 80

Energy Analytics Data Machine Learning 80

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. Data engineer. Business systems analyst.

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. Data engineer. Business systems analyst.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

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

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 72

Open Source Tools Data Engineering Storage 72

Altexsoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

Kentik

MAY 10, 2023

A unified data repository (UDR) is a centralized storage system that consolidates, organizes, and manages data from different sources. It serves as a single point of access for various types of data, which could be a significant volume of very diverse data formats in an extensive network. Why do we need a UDR?

Analytics 59

Analytics Network Data Machine Learning 59

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%). On-prem infrastructure will grow cold — with the exception of storage, Nardecchia says.

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Budget Artificial Inteligence Technical Review VR 363

CIO

JULY 15, 2022

The forecasting systems DTN had acquired were developed by different companies, on different technology stacks, with different storage, alerting systems, and visualization layers. Working with his new colleagues, he quickly identified rebuilding those five systems around a single forecast engine as a top priority.

Systems Review 279

Systems Review Fractional CTO System Development Team Review 279

CIO

FEBRUARY 14, 2023

This has also accelerated the execution of edge computing solutions so compute and real-time decisioning can be closer to where the data is generated. AI continues to transform customer engagements and interactions with chatbots that use predictive analytics for real-time conversations. report they have established a data culture 26.5%

Artificial Inteligence 290

Artificial Inteligence Strategy Data Machine Learning 290

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 83

Data Scalability Analytics Quality Assurance 83

The Crazy Programmer

NOVEMBER 6, 2021

A cloud architect has a profound understanding of storage, servers, analytics, and many more. Big Data Engineer. Another highest-paying job skill in the IT sector is big data engineering. And as a big data engineer, you need to work around the big data sets of the applications.

Artificial Inteligence 290

Artificial Inteligence Blockchain Software Review Artificial Intelligence 290

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 66

Open Source Analytics Software Review Metrics 66

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. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

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

Altexsoft

NOVEMBER 9, 2021

If you want to streamline your procurement and gain more visibility into this process, you have to get hold of available data, analyze it, and extract value to make informed decisions. What is procurement analytics and the opportunities it offers? Main components of procurement analytics. Procurement and its challenges.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

AWS Machine Learning - AI

JULY 15, 2024

Data intake A user uploads photos into Mixbook. The raw photos are stored in Amazon Simple Storage Service (Amazon S3). The data intake process involves three macro components: Amazon Aurora MySQL-Compatible Edition , Amazon S3, and AWS Fargate for Amazon ECS. DJ Charles is the CTO at Mixbook.

Generative AI 107

Generative AI Artificial Inteligence AWS Technical Review 107

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

Xebia

JULY 29, 2024

Data Modelers: They design and create conceptual, logical, and physical data models that organize and structure data for best performance, scalability, and ease of access. In the 1990s, data modeling was a specialized role. This ensures that documentation is always up-to-date and evolves alongside the project.

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