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. What is a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

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

Cloudera

JANUARY 12, 2018

I mentioned in an earlier blog titled, “Staffing your big data team, ” that data engineers are critical to a successful data journey. That said, most companies that are early in their journey lack a dedicated engineering group. Image 1: Data Engineering Skillsets.

Data Engineering 56

Data Engineering Big Data Engineering Data 56

CIO

FEBRUARY 13, 2023

Fifty-two percent of organizations plan to increase or maintain their IT spending this year, according to Enterprise Strategy Group. This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%).

Budget 363

Budget Artificial Inteligence Technical Review VR 363

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. From architectures and databases to feature stores and feature engineering, a myriad of variables must work in sync for this to be accomplished.

Artificial Inteligence 289

Artificial Inteligence Strategy Data Machine Learning 289

Altexsoft

FEBRUARY 11, 2023

To get a better understanding of a data architect’s role, let’s clear up what data architecture is. 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?

Data 87

Data Data Engineering Big Data Architecture 87

CIO

SEPTEMBER 2, 2022

Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications. Job duties include helping plan software projects, designing software system architecture, and designing and deploying web services, applications, and APIs. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

AUGUST 31, 2022

Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications. Job duties include helping plan software projects, designing software system architecture, and designing and deploying web services, applications, and APIs. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

TechCrunch

MAY 18, 2022

When asked, Heartex says that it doesn’t collect any customer data and open sources the core of its labeling platform for inspection. “We’ve built a data architecture that keeps data private on the customer’s storage, separating the data plane and control plane,” Malyuk added.

Open Source 203

Open Source Weak Development Team Artificial Inteligence Data 203

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

Cloudera

FEBRUARY 1, 2024

The other half of the equation requires your team’s emphasis to shift to sustained excellence in managing and optimizing your data ecosystem — better known as Day 2 operations. In this blog, we’ll cover the highlights of our recently published Day 2 Operations Guide and why it matters to enterprises.

Backup 85

Backup Cloud Architecture Resources 85

RapidValue

JULY 21, 2019

From DevOps to DataOps DataOps can be simply stated as “DevOps for data”. It is a set of practices and technologies that integrate the development and operation of data movement architectures into a continuous process. DataOps aids data practitioners to continuously deliver quality data to applications and business processes.

Business Transformation 65

Business Transformation Enterprise DevOps Analytics 65

Cloudera

JULY 27, 2021

While billing used to be one of two critical things for any successful telco (the other being the network), today’s digital service providers prioritise channels, ecosystems, payments and cloud service architectures in enterprise architecture. Edge analytics by definition require in-network deployment.

Telecommunications 62

Telecommunications Data Architecture Big Data 62

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data 94

Data Analytics Open Source Architecture 94

AWS Machine Learning - AI

JANUARY 26, 2024

Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

Artificial Inteligence 119

Artificial Inteligence Generative AI Security Applications 119

Cloudera

DECEMBER 10, 2020

CDW includes two highly scalable and performant Apache open-source engines – Impala and Hive LLAP – that have proven themselves in hundreds of enterprises for business-critical data warehousing. 150 for storage use = $15 / TB / month x 10 TB. 150 for storage use = $15 / TB / month x 10 TB.

Data 98

Data Technical Review Storage Systems Review 98

O'Reilly Media - Data

APRIL 3, 2018

Data Science and Machine Learning sessions will cover tools, techniques, and case studies. This year, we have many sessions on managing and deploying models to production, and applications of deep learning in enterprise applications. Data platforms. Privacy and security. Text and Natural Language sessions.

Machine Learning 155

Machine Learning Artificial Inteligence Company Case Study 155

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

Hu's Place - HitachiVantara

JANUARY 3, 2019

Data curation will be a focus 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 to power the organization.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data 85

Data Analytics Cloud Technical Review 85

Altexsoft

SEPTEMBER 9, 2022

Metadata management is a set of activities, technologies, and policies that target metadata collection, storage, and organizing. It aims at making data assets understandable and discoverable for users. Plus, a data fabric architecture design approach is also based on metadata as one of the main building blocks.

Tools 59

Tools Technical Review Software Review Systems Review 59

TIBCO - Connected Intelligence

DECEMBER 11, 2020

We have been working with TIBCO for over 18 years, initially focused on enterprise application integration, service-oriented architecture, events, messaging, and other capabilities that optimize our client’s operations. Tell me about your TIBCO partnership. “We

Business Transformation 52

Business Transformation Data Analytics Hotels 52

Altexsoft

APRIL 13, 2023

Due to extensive usage of connected IoT devices and advanced processing technologies, SCCTs not only gather data and build operational reports but also create predictions, define the impact of various macro- and microeconomic factors on the supply chain, and run “what-if” scenarios to find the best course of action.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Cloudera

SEPTEMBER 1, 2020

The CrunchIndexerTool can use Spark to read data from HDFS files into Apache Solr for indexing, and run the data through a so-called morphline for extraction and transformation in an efficient way. It is also possible to use CDP Data Hub Data Flow for real-time events or log data coming in that you want to make searchable via Solr.

Data 69

Data Backup Disaster Recovery Storage 69

Altexsoft

AUGUST 25, 2020

Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data. Prominent enterprises in numerous sectors including sales, marketing, research, and healthcare are actively collecting big data. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

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

Cloudera

AUGUST 30, 2022

Agencies are plagued by a wide range of data formats and storage environments—legacy systems, databases, on-premises applications, citizen access portals, innumerable sensors and devices, and more—that all contribute to a siloed ecosystem and the data management challenge. . Modern data architectures. Forrester ).

Architecture 80

Architecture Data Artificial Inteligence Artificial Intelligence 80

Cloudera

SEPTEMBER 10, 2021

Shared Data Experience ( SDX ) on Cloudera Data Platform ( CDP ) enables centralized data access control and audit for workloads in the Enterprise Data Cloud. The public cloud (CDP-PC) editions default to using cloud storage (S3 for AWS, ADLS-gen2 for Azure).

Storage 84

Storage Cloud Azure Pharmaceuticals 84

Altexsoft

OCTOBER 24, 2019

While our brain is both the processor and the storage, companies need multiple tools to work with data. And one of the most important ones is a data warehouse. In this article, we will discuss what an enterprise data warehouse is, its types and functions, and how it’s used in data processing.

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two. What data mesh IS.

Architecture 52

Architecture Data Analytics Data Engineering 52

Cloudera

MARCH 23, 2022

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. By being a truly open table format, Apache Iceberg fits well within the vision of the Cloudera Data Platform (CDP). 1: Multi-function analytics .

Data 93

Data Open Source Storage Machine Learning 93

Cloudera

APRIL 26, 2023

Can you achieve similar outcomes with your on-premises data platform? Application modernization initiatives have led to cloud native architectures gaining popularity on premises, making it a sensible choice to extend to your data platform. This is exactly where cloud native architectures excel, and why they are so popular.

Cloud 65

Cloud Data Load Balancer Storage 65

Kentik

APRIL 11, 2016

Clustered computing for real-time Big Data analytics. The concept of parallel processing based on a “clustered” multi-computer architecture has a long history dating back at least as far as Gene Amdahl’s work at IBM in the 1960s. For more on how we make it work, see Inside the Kentik Data Engine.).

Big Data 40

Big Data Analytics Network Architecture 40

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

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

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. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

Strategy Driven

AUGUST 27, 2015

The Internet and cloud computing have revolutionized the nature of data capture and storage, tempting many companies to adopt a new 'Big Data' philosophy: collect all the data you can; all the time. Copyright 2007-2015 by StrategyDriven Enterprises, LLC. All rights reserved.

Big Data 33

Big Data Data Storage Journal 33