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. Feature engineering.

Data Engineering 98

Data Engineering Engineering Data Artificial Inteligence 98

Cloudera

JANUARY 20, 2021

STEP 3: Monitor data throughput from each factory. With all the data now flowing into individual Kafka streams, a data architect is monitoring data throughput from each factory as well as adjusting compute and storage resources needed to make sure that each factory has the required throughput to send data into the platform.

Data 114

Data Artificial Inteligence Analytics Machine Learning 114

O'Reilly Media - Data

JULY 18, 2018

We also know exactly how much it costs to build training data sets from scratch. With the rise of data-hungry methods like deep learning, there is growing demand for services like Figure Eight and Mighty AI that help companies label images, video, and other data sources. control over how their data is shared and used.

Artificial Inteligence 144

Artificial Inteligence Machine Learning Data Marketing 144

Erik Bernhardsson

DECEMBER 15, 2020

Decades ago, software engineering was hard because you had to build everything from scratch and solve all these foundational problems. You need storage to build something to serve 1M concurrent users? For instance: internet first created DVD-by-mail, but the real internet-native innovation was streaming video.).

Software Engineering 325

Software Engineering Engineering Tools Software 325

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 86

Data Analytics Cloud Technical Review 86

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

O'Reilly Media - Ideas

MARCH 31, 2020

Your division is starting a new video streaming service and you’re tasked with building a system to recommend movies. There may even be someone on your team who built a personalized video recommender before and can help scope and estimate the project requirements using that past experience as a point of reference.

Product Management 138

Product Management Artificial Inteligence Machine Learning Weak Development Team 138

Kentik

MAY 23, 2017

Imagine a big data time-series datastore that unifies traffic flow records (NetFlow, sFlow, IPFIX) with related data such as BGP routing, GeoIP, network performance, and DNS logs, that retains unsummarized data for months, and that has the compute and storage power to answer ad hoc queries across billions of data points in a couple of seconds.

Network 40

Network Open Source Big Data Load Balancer 40

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

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.

Big Data 33

Big Data Data Storage Journal 33

Kentik

APRIL 4, 2023

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. In this case, choosing to separate the storage traffic from the normal business traffic enhances both performance and reliability.

Network 104

Network Load Balancer Cloud Backup 104

Altexsoft

JUNE 6, 2019

If you change your mind about that cupcake, just put it back – our technology will update your virtual cart automatically,” explains the official video. Promotional video of self-service kiosks. The solution is purchasable through HikVision video surveillance equipment provider and manageable via the HikCentral platform.

Artificial Inteligence 89

Artificial Inteligence Artificial Intelligence Retail Innovation 89

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

Altexsoft

APRIL 16, 2021

An overview of data warehouse types. Optionally, you may study some basic terminology on data engineering or watch our short video on the topic: What is data engineering. What is data pipeline. This could be a transactional database or any other storage we take data from.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

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

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

Altexsoft

JUNE 26, 2023

Both data integration and ingestion require building data pipelines — series of automated operations to move data from one system to another. For this task, you need a dedicated specialist — a data engineer or ETL developer. Data engineering explained in 14 minutes. Decide on a sufficient data amount.

Artificial Inteligence 52

Artificial Inteligence Machine Learning Data Systems Review 52

Altexsoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. 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. What is Hadoop? Apache Hadoop architecture.

Big Data 59

Big Data Data Google Cloud Open Source 59

Altexsoft

APRIL 26, 2022

The data journey from different source systems to a warehouse commonly happens in two ways — ETL and ELT. The former extracts and transforms information before loading it into centralized storage while the latter allows for loading data prior to transformation. Each node has its own disk storage. Database storage layer.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

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

MARCH 16, 2021

In general, a data infrastructure is a system of hardware and software tools used to collect, store, transfer, prepare, analyze, and visualize data. Check our article on data engineering to get a detailed understanding of the data pipeline and its components. Big data infrastructure in a nutshell.

Big Data 116

Big Data Healthcare Applications Data 116

Cloudera

NOVEMBER 2, 2020

It has the key elements of fast ingest, fast storage, and immediate querying for BI purposes. Basic Architecture for Real-Time Data Warehousing. These include stream processing/analytics, batch processing, tiered storage (i.e. for active archive or joining live data with historical data), or machine learning.

Data 101

Data Analytics Storage Big Data 101

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 Machine Learning 52

Altexsoft

SEPTEMBER 10, 2021

It involves combining data from disparate sources, removing its redundancies, cleaning up any errors, and aggregating it within a single data store like a data warehouse. The delivery style to consolidate data is common data storage we’re covering below. How data consolidation works.

Tools 52

Tools Data Software Review Technical Review 52

Altexsoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. Data storage and processing.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. A topic, in turn, is divided into partitions — the smallest units of storage space, hosting an ordered sequence of messages. By the way, you can watch our video to understand how APIs work in general.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

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. Virtually, Hadoop puts no limits on the storage capacity. HDFS: a storage layer.

Big Data 98

Big Data Tools Data Storage 98

Altexsoft

NOVEMBER 9, 2021

Check a brief video explaining how demand forecasting works. Digitization has already greatly improved this business aspect, facilitating contract creation and editing, introducing e-signatures, increasing security, tracking expiration dates, and enabling convenient search and storage functionalities. Extract data. Process data.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Altexsoft

FEBRUARY 22, 2022

It’s an awful lot of data, so it has to be processed with special tools. Processing data. Telematics data is generated continuously in enormous amounts so it falls under the category of big data. It requires building a complex storage, processing, and analysis architecture.

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

DECEMBER 14, 2022

A container engine acts as an interface between the containers and a host operating system and allocates the required resources. Containers require fewer host resources such as processing power, RAM, and storage space than virtual machines. Docker also offers video explainers for those who prefer to listen and watch instead of reading.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Altexsoft

AUGUST 4, 2021

For example, a company has a data mart containing all the financial data. The company may wish to model an OLAP cube to summarize this data by different dimensions: by time, by product, or by city, to name a few. Watch our video about data engineering to learn more about how data gets from sources to BI tools.

Data 64

Data Analytics Construction Cloud 64

Kentik

JUNE 4, 2019

By correlating an ever-wider set of traffic data into a single, instantly-queryable dataset (the Kentik Data Engine, aka KDE), we’re able to generate technical and business insights with direct, powerful relevance to your network operations. Understanding Our Video Traffic. How True Origin Works.

Video 56

Video Network Internet Groups 56

Altexsoft

OCTOBER 3, 2019

A provider maintains the platform and handles the storage of your data. Data engineer builds interfaces and infrastructure to enable access to data. So, data engineers make data pipelines work. Data warehouse developer models, develops, and maintains data storages.

Analytics 16

Analytics Company Off-The-Shelf How To 16

Kentik

MAY 31, 2017

It’s high time to move away from this legacy paradigm to a unified, scalable, real-time solution built on the power of big data. Today’s siloed network management tools can be traced back to an earlier era, when design was constrained by the limited computing, memory, and storage capacity of appliances or single-server software deployments.

Network 40

Network Tools Big Data Engineering 40

Altexsoft

MARCH 2, 2023

Essentially, the fundamental principle underlying this process is to recognize data as a valuable resource, given its significant role in driving business success. Data management is a technical implementation of data governance and involves the practical aspects of working with data, such as data storage, retrieval, and analysis.

Government 52

Government Tools Data Weak Development Team 52

Kentik

JUNE 26, 2017

The first organization decided to build with straw… that is, with a single-server software architecture using a relational database like mySQL to contain the data. Its walls were made of thin stalks of memory, CPU, and storage. This enhanced data is stored in a massive, scale-out infrastructure with Petabytes of capacity.

Big Data 40

Big Data Architecture Analytics Storage 40

Altexsoft

DECEMBER 9, 2020

Sometimes, a data or business analyst is employed to interpret available data, or a part-time data engineer is involved to manage the data architecture and customize the purchased software. At this stage, data is siloed, not accessible for most employees, and decisions are mostly not data-driven.

Analytics 102

Analytics Technical Review Technology Applications 102