Openxcell

JANUARY 6, 2023

Instead of making substantial investments in databases, software, and hardware, businesses prefer to access their computing power over the internet or in the cloud. Just a few of the existing cloud services include servers, storage, databases, networking, software, analytics, and business intelligence. ServerSpace.

Architecture 52

Architecture Cloud Storage Google Cloud 52

CTOvision

FEBRUARY 4, 2015

If you are into technology and government and want to find ways to enhance your ability to serve big missions you need to be at this event, 25 Feb at the Hilton McLean Tysons Corner. Big data and its effect on the transformative power of data analytics are undeniable. Enabling Business Results with Big Data.

Fractional CTO 134

Fractional CTO Technical Review Big Data Analytics 134

CTOvision

JANUARY 18, 2015

This popular gathering is designed to enable dialogue about business and technical strategies to leverage today’s big data platforms and applications to your advantage. Big data and its effect on the transformative power of data analytics are undeniable. Enabling Business Results with Big Data.

Fractional CTO 113

Fractional CTO Program Management Programming Big Data 113

CTOvision

JANUARY 19, 2014

The place for enterprises to store all data with enterprise grade data management and protection, with access by any system (from legacy to modern, from proprietary to open source). This is the big data news of 2013, from a technology perspective. Business Intelligence 2.0:

Technical Review 109

Technical Review Technology Business Intelligence Systems Review 109

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

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 Open Source 59

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

Apiumhub

AUGUST 12, 2021

This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.

Industry 59

Industry Technical Advisors CTO Coach Azure 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

CIO

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI).

Data 350

Data Technical Advisors Artificial Inteligence Technical Review 350

Altexsoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Storage IoT 52

Altexsoft

OCTOBER 21, 2022

In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. Plus the name sounded cool for an open-source project.”.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Existek

JANUARY 27, 2023

Another trend expected to shape software development in the financial services industry is the increasing use of open-source software. Open-source software offers several benefits, such as lower costs, a wider pool of developers, and greater flexibility.

Software Development 52

Software Development Trends Technology Software 52

Altexsoft

APRIL 16, 2021

Namely, we’ll explain what functions it can perform, and how to use it for data analysis. As the topic is closely related to business intelligence (BI) and data warehousing (DW), we suggest you to get familiar with general terms first: A guide to business intelligence. An overview of data warehouse types.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

Altexsoft

FEBRUARY 10, 2021

New approaches arise to speed up the transformation of raw data into useful insights. Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. This approach to data workflow management was first taken by Airbnb.

Analytics 75

Analytics DevOps Development Software Review 75

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. Data size and type.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Altexsoft

FEBRUARY 24, 2023

Kubernetes or K8s for short is an open-source platform to deploy and orchestrate a large number of containers — packages of software, with all dependencies, libraries, and other elements necessary to execute it, no matter the environment. Source: Dynatrace What auxiliary processes do companies entrust to the orchestrator?

Weak Development Team 83

Weak Development Team Load Balancer Technical Review Microservices 83

Altexsoft

DECEMBER 14, 2022

Docker is an open-source containerization software platform: It is used to create, deploy and manage applications in virtualized containers. Launched in 2013 as an open-source project, the Docker technology made use of existing computing concepts around containers, specifically the Linux kernel with its features.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

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

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. On-premise data integration tools. Open-source data integration tools.

Tools 52

Tools Data Software Review Open Source 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. Data warehousing in a nutshell. Snowflake architecture overview.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Hu's Place - HitachiVantara

FEBRUARY 15, 2019

In the case of Hybrid and multi-cloud, we are mixing up multiple clouds which increases operational and data management complexity. Operational policies and methods are different and aggregation of data across multiple clouds boundaries makes it difficult for governance, analytics, and business intelligence.

Cloud 49

Cloud AWS Open Source Data Center 49

Altexsoft

JUNE 20, 2019

What are their main advantages and disadvantages, and how should businesses use them? Originally being an open-source solution, MySQL now is owned by Oracle Corporation. Partial open-source. Although MySQL has the open-source part, it’s mostly under Oracle’s license. Let’s take a deeper look.

Systems Review 85

Systems Review System Software Review Open Source 85

Altexsoft

SEPTEMBER 21, 2023

In this edition of “The Good and The Bad” series, we’ll dig deep into Elasticsearch — breaking down its functionalities, advantages, and limitations to help you decide if it’s the right tool for your data-driven aspirations. Key components of the Elasticsearch architecture. What is Elasticsearch?

Weak Development Team 52

Weak Development Team Analytics Engineering Development Team Review 52

Altexsoft

OCTOBER 2, 2020

Key disciplines and roles in data management. Data architecture: aligning technologies with business goals. Specialist responsible for the area: data architect. Data architecture is a starting point for any data management model. Snowflake data management processes.

Strategy 64

Strategy Database Administration Data Technical Review 64

CIO

JANUARY 20, 2023

2] Foundational considerations include compute power, memory architecture as well as data processing, storage, and security. It’s About the Data For companies that have succeeded in an AI and analytics deployment, data availability is a key performance indicator, according to a Harvard Business Review report. [3]

Analytics 342

Analytics Artificial Inteligence Artificial Intelligence Hardware 342

O'Reilly Media - Ideas

MAY 21, 2019

We found that companies that have successfully adopted machine learning do so either by building on existing data products and services, or by modernizing existing models and algorithms. Use ML to unlock new data types—e.g., Thus, many developers will need to curate data, train models, and analyze the results of models.

Artificial Inteligence 97

Artificial Inteligence Machine Learning Technical Review Technology 97

Altexsoft

MARCH 30, 2023

It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data. The relatively new storage architecture powering Databricks is called a data lakehouse. Databricks lakehouse platform architecture.

Weak Development Team 64

Weak Development Team Artificial Inteligence Machine Learning Software Review 64

Altexsoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it.

Data 59

Data Technical Review Software Review Open Source 59

Apiumhub

MARCH 4, 2021

DaaS leverages the popular software-as-a-service (SaaS) paradigm, through which customers are able to use cloud-based software applications delivered over the network rather than deploying dedicated hardware servers for a specific set of tasks on a specific set of data. Business intelligence.

Trends 72

Trends Data Analytics Business Intelligence 72