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

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

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

CIO

OCTOBER 9, 2024

The data preparation process should take place alongside a long-term strategy built around GenAI use cases, such as content creation, digital assistants, and code generation. Known as data engineering, this involves setting up a data lake or lakehouse, with their data integrated with GenAI models.

Strategy 215

Strategy Data Artificial Inteligence Storage 215

CIO

APRIL 10, 2024

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 funneled through RAG must be efficient, scalable, and optimized to make GenAI applications useful. Inferencing and… Sherlock Holmes???

Artificial Inteligence 203

Artificial Inteligence Generative AI Storage Artificial Intelligence 203

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

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

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 85

Data Engineering Performance Engineering Data 85

Netflix Tech

DECEMBER 21, 2020

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 84

Storage Data Resources Data Engineering 84

AWS Machine Learning - AI

NOVEMBER 20, 2024

The solution combines data from an Amazon Aurora MySQL-Compatible Edition database and data stored in an Amazon Simple Storage Service (Amazon S3) bucket. Solution overview Amazon Q Business is a fully managed, generative AI-powered assistant that helps enterprises unlock the value of their data and knowledge.

Data 108

Data AWS Groups Knowledge Base 108

Perficient

MARCH 27, 2025

Deletion vectors are a storage optimization feature that replaces physical deletion with soft deletion. Ensuring compliant data deletion is a critical challenge for data engineering teams, especially in industries like healthcare, finance, and government. This could provide both cost savings and performance improvements.

Compliance 52

Compliance Systems Review Policies Storage 52

AWS Machine Learning - AI

NOVEMBER 15, 2024

The flexible, scalable nature of AWS services makes it straightforward to continually refine the platform through improvements to the machine learning models and addition of new features. All AWS services are high-performing, secure, scalable, and purpose-built.

Generative AI 111

Generative AI AWS Groups Artificial Inteligence 111

CIO

JUNE 19, 2024

Platform engineering: purpose and popularity Platform engineering teams are responsible for creating and running self-service platforms for internal software developers to use. AI is 100% disrupting platform engineering,” Srivastava says, so it’s important to have the skills in place to exploit that. “As

Weak Development Team 208

Weak Development Team Engineering UI/UX Software Development 208

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. It’s also used to deploy machine learning models, data streaming platforms, and databases. The features can be raw data that has been processed or analyzed or derived.

Artificial Inteligence 174

Artificial Inteligence Strategy Data Machine Learning 174

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

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. Is it still so?

Backup 115

Backup Azure Software Review Architecture 115

CIO

FEBRUARY 13, 2023

On-prem infrastructure will grow cold — with the exception of storage, Nardecchia says. Some storage will likely stay on-prem while more is pushed into the public cloud, he says. Fleschut says he will also hire more IT personnel this year, especially data scientists, architects, and security and risk professionals.

Budget 218

Budget Artificial Inteligence Technical Review VR 218

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 167

Systems Review Fractional CTO System Development Team Review 167

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

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. Focus on scalability. So, how do we achieve scalability?

Data 97

Data Scalability Storage Big Data 97

AWS Machine Learning - AI

MARCH 13, 2025

Amazon Bedrocks broad choice of FMs from leading AI companies, along with its scalability and security features, made it an ideal solution for MaestroQA. The customer interaction transcripts are stored in an Amazon Simple Storage Service (Amazon S3) bucket. The following architecture diagram demonstrates the request flow for AskAI.

Generative AI 68

Generative AI CTO Coach AWS Artificial Inteligence 68

CIO

SEPTEMBER 2, 2022

In the finance industry, software engineers are often tasked with assisting in the technical front-end strategy, writing code, contributing to open-source projects, and helping the company deliver customer-facing services. Data engineer.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CIO

AUGUST 31, 2022

In the finance industry, software engineers are often tasked with assisting in the technical front-end strategy, writing code, contributing to open-source projects, and helping the company deliver customer-facing services. Data engineer.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

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 101

Data Storage Architecture Big Data 101

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 116

Generative AI Artificial Inteligence AWS Technical Review 116

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. Data Users: These are analysts and BI developers who use data within the organization.

Technical Review 130

Technical Review Data Systems Review Meeting 130

Cloudera

NOVEMBER 28, 2023

Cloudera Private Cloud Data Services is a comprehensive platform that empowers organizations to deliver trusted enterprise data at scale in order to deliver fast, actionable insights and trusted AI. This means you can expect simpler data management and drastically improved productivity for your business users.

Data 84

Data Scalability Analytics Quality Assurance 84

AWS Machine Learning - AI

MARCH 13, 2025

This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team of GoDaddy Generative AI solutions have the potential to transform businesses by boosting productivity and improving customer experiences, and using large language models (LLMs) in these solutions has become increasingly popular.

Artificial Inteligence 94

Artificial Inteligence Systems Review System Generative AI 94

O'Reilly Media - Ideas

JANUARY 14, 2025

Building applications with RAG requires a portfolio of data (company financials, customer data, data purchased from other sources) that can be used to build queries, and data scientists know how to work with data at scale. Data engineers build the infrastructure to collect, store, and analyze data.

Trends 132

Trends Technology Security Artificial Inteligence 132

Xebia

JANUARY 30, 2025

In this blog post, we want to tell you about our recent effort to do metadata-driven data masking in a way that is scalable, consistent and reproducible. Using dbt to define and document data classifications and Databricks to enforce dynamic masking, we ensure that access is controlled automatically based on metadata.

Data 130

Data Groups Data Engineering Systems Review 130

Altexsoft

MARCH 18, 2021

This includes Apache Hadoop , an open-source software that was initially created to continuously ingest data from different sources, no matter its type. Cloud data warehouses such as Snowflake, Redshift, and BigQuery also support ELT, as they separate storage and compute resources and are highly scalable.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

AWS Machine Learning - AI

JUNE 18, 2024

The platform, although functional, deals with CSV and JSON files containing hundreds of thousands of rows from various manufacturers, demanding substantial effort for data ingestion. The objective is to automate data integration from various sensor manufacturers for Accra, Ghana, paving the way for scalability across West Africa.

Generative AI 121

Generative AI Artificial Inteligence Technical Review AWS 121

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

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

JANUARY 20, 2021

This table can be massively scaled to any use-case and this is why HBase is superior in this application as it’s a distributed, scalable, big data store. In order to use this data, I built a very simple demo using the popular Flask framework for building web applications. Serving The Model . GitHub Repo Link.

Machine Learning 115

Machine Learning Artificial Inteligence Applications Data 115

Perficient

FEBRUARY 28, 2023

In the first article in this series, I explained the five components necessary to prevent a Data Lake from Becoming a Data Swamp. Data lakes work on the concept of load first and use later, which means the data stored in the repository doesn’t necessarily have to be used immediately for a specific purpose.

Data 110

Data Analytics Google Cloud Cloud 110

Cloudera

APRIL 26, 2023

At its core, CDP Private Cloud Data Services (“the platform”) is an end-to-end cloud native platform that provides a private open data lakehouse. It offers features such as data ingestion, storage, ETL, BI and analytics, observability, and AI model development and deployment.

Cloud 64

Cloud Data Load Balancer Storage 64