Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Performance.

Big Data 63

Big Data Data Storage Microservices 63

KitelyTech

FEBRUARY 3, 2021

Big data and data science are important parts of a business opportunity. How companies handle big data and data science is changing so they are beginning to rely on the services of specialized companies. User data collection is data about a user who is collected for market research purposes.

Big Data 52

Big Data Data Development Business Intelligence 52

CIO

JUNE 7, 2022

Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. Data analysts and others who work with analytics use a range of tools to aid them in their roles.

Analytics 338

Analytics Data Analysis Business Analytics 338

Altexsoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data 87

Data Data Engineering Big Data Architecture 87

Xebia

MAY 16, 2023

Data Engineers were tempted by the pressure of the moment to give up on testing all together. There was no need for generating your own data; just take a percentage of production data. In many cases, these tasks ended up on the shoulders of the Data Engineers themselves. Overly restrictive governance.

Testing 130

Testing How To Data Engineering Engineering 130

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. The features can be raw data that has been processed or analyzed or derived. The ML workflow for creating these features is referred to as feature engineering.

Artificial Inteligence 290

Artificial Inteligence Strategy Data Machine Learning 290

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

Dzone - DevOps

FEBRUARY 16, 2023

So in this article, I will talk about how I improved overall data processing efficiency by optimizing the choice and usage of data warehouses. Too Much Data on My Plate The choice of data warehouses was never high on my worry list until 2021. In the company's infancy, we didn't have too much data to juggle.

Data 71

Data ChatGPT Storage Architecture 71

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

Kentik

JULY 18, 2016

Seeing Beneath the Surface with Post-Hadoop Big Data. At Kentik, we believe deeply in the power of post-Hadoop Big Data to address those limitations, making rich data readily accessible not only to engineering and operations, but also to wider areas of the organization. Dig deep without a backhoe.

Big Data 40

Big Data Network Analytics Data 40

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 is Not Just More Data : That’s because the nature of the data we can now collect has changed.

Big Data 33

Big Data Data Storage Journal 33

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. Who needs a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

Cloudera

JULY 14, 2023

Introduction For more than a decade now, the Hive table format has been a ubiquitous presence in the big data ecosystem, managing petabytes of data with remarkable efficiency and scale. Depending on the size and usage patterns of the data, several different strategies could be pursued to achieve a successful migration.

Backup 69

Backup Data Engineering Engineering Data 69

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

JUNE 18, 2022

As use cases matured, we saw the need for both efficient, interactive BI analytics and transactional semantics to modify data. The first generation of the Hive Metastore attempted to address the performance considerations to run SQL efficiently on a data lake. More formats, more engines, more interoperability.

Data 89

Data Analytics Open Source Architecture 89

Hu's Place - HitachiVantara

MAY 10, 2019

For this reason, many financial institutions are converting their fraud detection systems to machine learning and advanced analytics and letting the data detect fraudulent activity. This will require another product for data governance. Data Preparation : Data integrationthat is intuitive and powerful.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

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

O'Reilly Media - Ideas

APRIL 9, 2019

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. Data engineering is not in the limelight.

Data Engineering 111

Data Engineering Engineering Data Technical Review 111

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Hybrid clouds must bond together the two clouds through fundamental technology, which will enable the transfer of data and applications. REAN Cloud is a global cloud systems integrator, managed services provider and solutions developer of cloud-native applications across big data, machine learning and emerging internet of things (IoT) spaces.

Cloud 78

Cloud Google Cloud Azure AWS 78

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

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. This blog post focuses on how the Kafka ecosystem can help solve the 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

Abhishek Tiwari

DECEMBER 22, 2017

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. Then we perform frequent batch ETL from application databases to a data warehouse. Classic ETL. Stateless and elastic.

Storage 40

Storage Big Data Google Cloud Analysis 40

Kentik

MAY 23, 2017

Given the advanced capabilities provided by cloud and big data technology, there’s no longer any justification for legacy monitoring appliances that summarize away all the details and force operators to swivel between siloed tools. ISPs can gain similar advantages by becoming far more data driven.

Network 40

Network Open Source Big Data Load Balancer 40

Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

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 80

Data Analytics Cloud Technical Review 80

AWS Machine Learning - AI

JANUARY 26, 2024

We are committed to expanding our capabilities to allow you to meet your digital sovereignty needs, without compromising on the performance, innovation, security, or scale of the AWS Cloud. Understand the security posture of your AI, ML, and generative AI workloads by performing a Well-Architected Framework review.

Artificial Inteligence 118

Artificial Inteligence Generative AI Security Applications 118

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. Graph processing.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Netflix Tech

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. 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

Hu's Place - HitachiVantara

SEPTEMBER 26, 2018

The music industry was panicked over the loss of revenue, but today the music industry is making more money than ever due to live performances which are promoted by their music. Data bases were great at solving puzzles, but the complex nature of today’s business is more of a mystery that requires big data and analytics.

Software Review 60

Software Review Systems Review Technical Review Big Data 60

Altexsoft

OCTOBER 29, 2020

But before you dive in, we recommend you reviewing our more beginner-friendly articles on data transformation: Complete Guide to Business Intelligence and Analytics: Strategy, Steps, Processes, and Tools. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

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

JANUARY 20, 2021

In order to enable connected manufacturing and emerging IoT use cases, ECC needs a solution that can handle all types of diverse data structures and schemas from the edge, normalize the data, and then share it with any type of data consumer including Big Data applications. . STEP 1: Collecting the raw data.

Data 103

Data Artificial Inteligence Analytics Machine Learning 103

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

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

Existek

JANUARY 11, 2022

In 2010, they launched Windows Azure, the PaaS, positioning it as an alternative to Google App Engine and Amazon EC2. They provided a few services like computing, Azure Bob storage, SQL Azure, and Azure Service Bus. The new structure enabled the opportunity to meet such customer needs in computing as storage, networking, and services.

Azure 52

Azure AWS Cloud How To 52

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. Data lineage graph. Source: Oracle.

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

AUGUST 19, 2022

Marketing departments can track how successful their campaigns perform, predict customer churn , and conduct sentiment analysis. Executives and managers can use the platform to monitor the overall company performance, discover important market trends, and run what-if scenarios to make most effective strategic decisions.

Weak Development Team 52

Weak Development Team Data Azure Analytics 52