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

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

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.

Artificial Inteligence 106

Artificial Inteligence Machine Learning Scalability Data Engineering 106

Apps Associates

JULY 28, 2022

Use Case 1: Data integration for big data, data lakes, and data science. Efficiently load and transform data at scale into Data Lakes for data science and analytics. Load the data into object storage and create high-quality models more quickly using OCI data science.

Infrastructure 52

Infrastructure Cloud Data Linux 52

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.

Artificial Inteligence 116

Artificial Inteligence Machine Learning Applications Data 116

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 Artificial Inteligence 52

Altexsoft

MARCH 16, 2021

In this article, we will explain the concept and usage of Big Data in the healthcare industry and talk about its sources, applications, and implementation challenges. What is Big Data and its sources in healthcare? So, what is Big Data, and what actually makes it Big? Let’s see where it can come from.

Big Data 116

Big Data Healthcare Applications Data 116

Existek

JANUARY 11, 2022

And companies that have completed it emphasize gained advantages like accessibility, scalability, cost-effectiveness, etc. . In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2.

Azure 52

Azure AWS Cloud How To 52

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics.

Weak Development Team 52

Weak Development Team Big Data Data Artificial Inteligence 52

d2iq

FEBRUARY 19, 2021

Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

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

Altexsoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics.

Big Data 59

Big Data Data Google Cloud Storage 59

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 81

Storage Data Resources Data Engineering 81

Altexsoft

SEPTEMBER 9, 2022

In data science , metadata is one of the central aspects: It describes data (including unstructured data streams) fed into a big data analytical platform, capturing, for example, formats, file sizes, source of information, permission details, etc. Metadata storage. Types of metadata.

Tools 59

Tools Technical Review Software Review Systems Review 59

CIO

JUNE 14, 2023

Big data exploded onto the scene in the mid-2000s and has continued to grow ever since. Today, the data is even bigger, and managing these massive volumes of data presents a new challenge for many organizations. Even if you live and breathe tech every day, it’s difficult to conceptualize how big “big” really is.

Data 157

Data Scalability Storage Big Data 157

Perficient

FEBRUARY 16, 2024

In the world of big data processing, efficient and scalable file systems play a crucial role. DBFS is a distributed file system that comes integrated with Databricks, a unified analytics platform designed to simplify big data processing and machine learning tasks. What is DBFS? How does DBFS work?

System 52

System Storage Azure Big Data 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. Scalability.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

AWS Machine Learning - AI

JANUARY 26, 2024

Next, make sure that all data at rest is encrypted with AWS KMS, including considering the use of CMKs, and all data and models are versioned and backed up using Amazon Simple Storage Service (Amazon S3) versioning and applying object-level immutability with Amazon S3 Object Lock.

Artificial Inteligence 115

Artificial Inteligence Generative AI Security Applications 115

Altexsoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Which Big Data tasks does Spark solve most effectively? scalability.

Big Data 98

Big Data Tools Data Storage 98

Kentik

SEPTEMBER 11, 2015

About Foreign Data Wrappers. Relational databases like PostgreSQL (PG) have long been dominant for data storage and access, but sometimes you need access from your application to data that’s either in a different database format, in a non-relational database, or not in a database at all. Setting the Environment.

Data 40

Data Authentication Data Engineering Scalability 40

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview. Stream processing.

Analytics 20

Analytics Data IoT Analysis 20

ParkMyCloud

JANUARY 17, 2020

Individuals in an associate solutions architect role have 1+ years of experience designing available, fault-tolerant, scalable, and most importantly cost-efficient, distributed systems on AWS. Must prove knowledge of deploying, operating and managing highly available, scalable and fault-tolerant systems on AWS. Azure Fundamentals.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Altexsoft

MARCH 18, 2021

As data keeps growing in volumes and types, the use of ETL becomes quite ineffective, costly, and time-consuming. Basically, ELT inverts the last two stages of the ETL process, meaning that after being extracted from databases data is loaded straight into a central repository where all transformations occur. ELT comes to the rescue.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

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 Systems Review 115

Cloudera

FEBRUARY 22, 2022

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists.

Data 112

Data Analytics Disaster Recovery Travel 112

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 102

Data Storage Architecture Big Data 102

Kentik

OCTOBER 25, 2016

How Scalable Architecture Boosts Accuracy in Detection. These issues are rooted in the inherent compute and storage limitations of scale-up detection architectures. Big data to the rescue. DDoS is a big data problem — too big for scale-up architecture. Monitor against multiple data dimensions.

Scalability 40

Scalability Architecture Big Data Network 40

Cloudera

AUGUST 20, 2021

The Cloudera Data Platform comprises a number of ‘data experiences’ each delivering a distinct analytical capability using one or more purposely-built Apache open source projects such as Apache Spark for Data Engineering and Apache HBase for Operational Database workloads.

Strategy 100

Strategy Data Technical Review Weak Development Team 100

Altexsoft

APRIL 26, 2022

With the consistent rise in data volume, variety, and velocity, organizations started seeking special solutions to store and process the information tsunami. This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance. Each node has its own disk storage. What is Snowflake?

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. Still, it’s the number one choice for data-driven companies, and here’re some reasons why.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Cloudera

NOVEMBER 2, 2020

Correlations across data domains, even if they are not traditionally stored together (e.g. real-time customer event data alongside CRM data; network sensor data alongside marketing campaign management data). The extreme scale of “big data”, but with the feel and semantics of “small data”.

Data 99

Data Analytics Storage Big Data 99

Kentik

MARCH 7, 2023

Solving these problems for distributed cloud networks has required a big data approach, ultimately resulting in the evolution of network observability. Rich context and real-time datasets allow network engineers to dynamically filter, drill down, and map networks as queries adjust. Leverage automated insights and response flows.

Network 99

Network Cloud Data Case Study 99

Altexsoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Artificial Inteligence 52

Artificial Inteligence Machine Learning Data Systems Review 52

Altexsoft

OCTOBER 8, 2021

But more often than not data is scattered across a myriad of disparate platforms, databases, and file systems. What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data. Data integration process. As a rule, good data integration products have.

Tools 52

Tools Data Software Review Open Source 52

Hu's Place - HitachiVantara

MARCH 18, 2019

The requirement was to centralize and archive the data collected from these endpoint devices while keeping with regulation requirements. Hitachi Vantara provided HCP object storage to replace traditional storage for ease of access, search and index, privacy regulations and hybrid cloud.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

Altexsoft

NOVEMBER 10, 2021

A data lakehouse , as the name suggests, is a new data architecture that merges data warehouse and data lake into a single whole, aiming at addressing each one’s limitations. In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes.

Architecture 52

Architecture Data Storage Artificial Inteligence 52