Kentik

JULY 10, 2018

Network data is big data. The collection of massive amounts of streaming telemetry requires a high-speed data pipeline for ingesting data in real time and distributing it to the appropriate monitoring and analytics tools.

Tools 45

Tools Cloud Big Data WAN 45

CTOvision

OCTOBER 18, 2013

With the continuous development of advanced infrastructure based around Apache Hadoop there has been an incredible amount of innovation around enterprise “Big Data” technologies, including in the analytical tool space. H2O by 0xdata brings better algorithms to big data. Mike really nailed it with that one.

Technical Review 99

Technical Review Analytics Technology Big Data 99

Apiumhub

MARCH 16, 2021

With more and more data available, it’s getting more difficult to focus on the information we really need and present it in an actionable way and that’s what business intelligence is all about. In this article we will talk about Business Intelligence tools, benefits & use cases. . What is Business Intelligence.

Business Intelligence 117

Business Intelligence Tools Artificial Inteligence Technical Review 117

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. Big data processing.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Altexsoft

FEBRUARY 8, 2021

diversity of sales channels, complex structure resulting in siloed data and lack of visibility. These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

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

Infinidat

MARCH 10, 2021

Re-Thinking the Storage Infrastructure for Business Intelligence. With digital transformation under way at most enterprises, IT management is pondering how to optimize storage infrastructure to best support the new big data analytics focus. Adriana Andronescu. Wed, 03/10/2021 - 12:42.

Business Intelligence 98

Business Intelligence Storage Infrastructure Artificial Inteligence 98

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

CIO

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Artificial Inteligence 246

Artificial Inteligence Data Artificial Intelligence Analytics 246

Altexsoft

JANUARY 22, 2020

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. A complete guide to business intelligence and analytics. The role of business intelligence developer.

Analytics 20

Analytics Data IoT Analysis 20

Cloudera

JULY 9, 2018

Most organizations struggle to unlock data science in the enterprise. To that end, Cloudera offers the Data Science Workbench, a collaborative, scalable, and highly extensible platform for data exploration, analysis, modeling, and visualization. Being able to scale up and scale down rapidly is key.

Machine Learning 41

Machine Learning Artificial Inteligence Data Analytics 41

Cloudera

NOVEMBER 19, 2020

In financial services, another highly regulated, data-intensive industry, some 80 percent of industry experts say artificial intelligence is helping to reduce fraud. Machine learning algorithms enable fraud detection systems to distinguish between legitimate and fraudulent behaviors. Fraudulent Activity Detection.

Government 115

Government Artificial Inteligence Machine Learning Data 115

Altexsoft

APRIL 23, 2019

But how to turn unstructured data chunks into something useful? The answer is business intelligence. We’ve already discussed a machine learning strategy. In this article, we will discuss the actual steps of bringing business intelligence into your existing corporate infrastructure.

Business Intelligence 93

Business Intelligence Analytics Tools Strategy 93

RapidValue

DECEMBER 7, 2020

With the addition of Oracle Analytics Cloud (OAC) , Oracle Cloud now has a PaaS solution that can manage all your data analytics requirements within one tool. It is a scalable, reliable, and secure cloud service with extensive analytics capabilities at a lower cost when compared to OBIEE. By, Dipin Manmadhan.

Business Intelligence 72

Business Intelligence Analytics Cloud How To 72

Apiumhub

APRIL 27, 2021

Nowadays, data scientists have become vital to organizations all over the world as companies seek to achieve bigger goals with data science than ever before. What is Data Mining. Association Association is a data mining technique related to statistics. Retailers, banks, manufacturers, health industry players, etc.

Artificial Inteligence 104

Artificial Inteligence Data Machine Learning Artificial Intelligence 104

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. Ensure its scalability and integrability. Types of metadata.

Tools 59

Tools Technical Review Software Review Systems Review 59

Datavail

JUNE 8, 2023

Data Summit 2023 was filled with thought-provoking sessions and presentations that explored the ever-evolving world of data. From the technical possibilities and challenges of new and emerging technologies to using Big Data for business intelligence, analytics, and other business strategies, this event had something for everyone.

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

Altexsoft

APRIL 13, 2023

You can read the details on them in the linked articles, but in short, data warehouses are mostly used to store structured data and enable business intelligence , while data lakes support all types of data and fuel big data analytics and machine learning. Scalability.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Kaseya

NOVEMBER 9, 2023

Cloud infrastructure Four integral elements define the backbone of cloud infrastructure: Servers: Servers are the core of cloud infrastructure, acting as the computational engines that process and deliver data, applications and services. The servers ensure an efficient allocation of computing resources to support diverse user needs.

Cloud 105

Cloud Disaster Recovery Artificial Inteligence Infrastructure 105

Altexsoft

MARCH 18, 2021

From the late 1980s, when data warehouses came into view, and up to the mid-2000s, ETL was the main method used in creating data warehouses to support business intelligence (BI). As data keeps growing in volumes and types, the use of ETL becomes quite ineffective, costly, and time-consuming. What is ELT?

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Scalability. ELT vs ETL.

Tools 52

Tools Software Review Systems Review Testing 52

Altexsoft

MAY 20, 2020

In addition to broad sets of tools, it offers easy integrations with other popular AWS services taking advantage of Amazon’s scalable storage, computing power, and advanced AI capabilities. Amazon claims that the module is scalable enough to handle over a billion devices, with each of them getting assigned a unique identity.

IoT 141

IoT Azure AWS Transportation 141

Kentik

FEBRUARY 14, 2023

What are the main features of a modern data platform? Data platforms offer enterprises a range of features: Data ingestion Data storage Data transformation Data modeling Data discovery Data observability Data security Business intelligence Data platform ingestion Useful data is generated at every layer of an application.

Network 52

Network Data Artificial Inteligence Analysis 52

Altexsoft

APRIL 26, 2022

Not long ago setting up a data warehouse — a central information repository enabling business intelligence and analytics — meant purchasing expensive, purpose-built hardware appliances and running a local data center. The Fail-safe feature allows for protecting and recovering historical data.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Another type of data storage — a data lake — tried to address these and other issues.

Architecture 52

Architecture Data Storage Machine Learning 52

Existek

JANUARY 27, 2023

For example, many financial institutions are now using artificial intelligence and machine learning to analyze customer data and identify new opportunities for growth. Financial services companies handle sensitive customer data, and a data breach can have severe consequences for the company and its customers.

Software Development 52

Software Development Trends Technology Software 52

Altexsoft

JANUARY 14, 2021

It is usually created and used primarily for data reporting and analysis purposes. Thanks to the capability of data warehouses to get all data in one place, they serve as a valuable business intelligence (BI) tool, helping companies gain business insights and map out future strategies. Scalability.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

DECEMBER 14, 2020

Unstructured data, on the other hand, offers more flexibility and scalability. The absence of the pre-defined purpose of unstructured data makes it super flexible as the information can be stored in various file formats. Yet, this data is subjective and more difficult to work with. Data teams to handle data.

Data 93

Data Artificial Inteligence Storage Analytics 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 91

Data Analytics Storage Big Data 91

Altexsoft

SEPTEMBER 21, 2023

In 2023, Elasticsearch introduced the Elasticsearch Relevance Engine (ESRE) , a powerful upgrade integrating AI and machine learning into search. Elasticsearch supports machine learning algorithms that can automatically model and analyze the behavior of your data in real time, providing valuable insights and predictions.

Weak Development Team 52

Weak Development Team Analytics Engineering Development Team Review 52

Altexsoft

SEPTEMBER 23, 2021

The main purpose of a DW is to enable analytics: It is designed to source raw historical data, apply transformations, and store it in a structured format. This type of storage is a standard part of any business intelligence (BI) system, an analytical interface where users can query data to make business decisions.

Architecture 52

Architecture Data Storage IoT 52

Altexsoft

DECEMBER 14, 2022

The heart and soul of Docker are containers — lightweight virtual software packages that combine application source code with all the dependencies such as system libraries (libs) and binary files as well as external packages, frameworks, machine learning models, and more. Scalability. Docker containers.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Hu's Place - HitachiVantara

FEBRUARY 15, 2019

Hybrid and Multi-cloud Benefits Hybrid and multi-cloud strategies offer flexibility, scalability, and agility by providing the freedom to choose where and how to deploy workloads, without the complexity and delays of acquiring and deploying infrastructure and operations resources.

Cloud 49

Cloud AWS Azure Data Center 49

Altexsoft

AUGUST 4, 2021

Instead of combing through the vast amounts of all organizational data stored in a data warehouse, you can use a data mart — a repository that makes specific pieces of data available quickly to any given business unit. What is a data mart? Data mart use cases. Just like display cases in a store.

Data 64

Data Analytics Construction Cloud 64

Datavail

JULY 31, 2019

Big data software companies that used to run their applications on Hadoop are now switching to Kubernetes. What’s behind the recent move from Hadoop to Kubernetes, and where is the big data landscape going in the future? Platforms like Hadoop were created during and for a different era in big data.

Development 8

Development Big Data Open Source Google Cloud 8

CIO

JANUARY 20, 2023

Here’s what to consider: Ingesting the data : To be able to analyze more data at greater speeds, organizations need faster processing via high-powered servers and the right chips for AI—whether CPUs or GPUs. Protecting the data : Cyber threats are everywhere—at the edge, on-premises and across cloud providers.

Analytics 311

Analytics Artificial Inteligence Artificial Intelligence Hardware 311