Xebia

JANUARY 19, 2023

. – AltexSoft All the data processing is done in Big Data frameworks like MapReduce, Spark and Flink. – Jesse Anderson The data engineering field could be thought of as a superset of business intelligence and data warehousing that brings more elements from software engineering.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

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

Altexsoft

APRIL 5, 2021

In recent history, the unprocessed and raw information that we call data has gained an increasing amount of traction due to companies realizing its potential. For a layman, this is exactly what started the buzz around big data. Only useable for data-oriented developers or analysts. Use Cases of ETL. Conclusion.

Company 78

Company Data Technical Review Analysis 78

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. Amazon Web Services (AWS).

Architecture 52

Architecture Cloud Storage Google Cloud 52

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

AUGUST 29, 2023

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. This article explains what a data lake is, its architecture, and diverse use cases. Who needs a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

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

Gorilla Logic

MAY 19, 2021

Not surprisingly, the skill sets companies need to drive significant enterprise software builds, such as big data and analytics, cybersecurity, and AI/ML, are among the most competitive. Some of the most common include cloud, IoT, big data, AI/ML, mobile, and more. Skill shortages can delay project kickoffs and delivery.

Software Review 94

Software Review Technical Review Software Development Team Review 94

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. data cataloging). Types of metadata.

Tools 59

Tools Technical Review Software Review Systems Review 59

Cloudera

NOVEMBER 19, 2020

November 15-21 marks International Fraud Awareness Week – but for many in government, that’s every week. From bogus benefits claims to fraudulent network activity, fraud in all its forms represents a significant threat to government at all levels. The Public Sector data challenge. Modernization has been a boon to government.

Government 115

Government Artificial Inteligence Machine Learning Data 115

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

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 298

Artificial Inteligence Data Artificial Intelligence Analytics 298

CTOvision

SEPTEMBER 9, 2016

Zoomdata develops the world’s fastest visual analytics solution for big data. Using patented data sharpening and micro-query technologies, Zoomdata empowers business users to visually consume data in seconds, even across billions of rows of data.

Big Data 60

Big Data Data Analytics Business Intelligence 60

CTOvision

SEPTEMBER 9, 2016

Zoomdata is the next generation data visualization system that easily allows companies and people to understand data visually in realtime. Zoomdata develops the world’s fastest visual analytics solution for big data. They are an In-Q-Tel company and a strategic investment in Zoomdata was announced on 8 Sep 2016.

Big Data 60

Big Data Data Analytics Scalability 60

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

Datavail

AUGUST 19, 2021

We’ve done a lot of research on this question, and we’ve compiled that research into a list of the most critical benefits organizations are looking for in terms of business intelligence (BI) systems that provide data analytics. Business leaders want the ability to do self-service data exploration and discovery.

Analytics 98

Analytics Data Business Intelligence Media 98

Perficient

MARCH 14, 2023

This means enabling teams to create accessible discovery sandboxes quickly and easily for ad-hoc exploration by power users and data scientists without sacrificing the necessary governance and security.

Data 64

Data Healthcare AWS Analytics 64

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. Data lake architecture example. Poor data quality, reliability, and integrity.

Architecture 52

Architecture Data Storage Machine Learning 52

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

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. As a rule, good data integration products have. high security. Source: Oracle.

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. The Fail-safe feature allows for protecting and recovering historical data.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

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. Structured data is modeled to be easily searchable and occupy minimal storage space.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Altexsoft

OCTOBER 2, 2020

Data analytics and business intelligence: drawing insights from data. Specialist responsible for the area: data analyst, business intelligence analyst, data scientist, marketing analyst. Business intelligence uses data for better decision-making regarding organizational operations.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Existek

JANUARY 27, 2023

Financial services companies handle sensitive customer data, and a data breach can have severe consequences for the company and its customers. Scalability is also a significant challenge for financial services software development. An automated Teller Machine (ATM) network is something we all access almost every day.

Software Development 52

Software Development Trends Technology Software 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

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. How do I wrangle in my data science community?

Machine Learning 41

Machine Learning Artificial Inteligence Data Analytics 41

Apiumhub

APRIL 27, 2021

However, making sense of the huge volumes of structured and unstructured data to implement organization-wide improvements can be extremely challenging because of the huge amount of information. What is Data Mining. Data mining is widely used in business , science research, and government security.

Artificial Inteligence 103

Artificial Inteligence Data Machine Learning Artificial Intelligence 103

Datavail

AUGUST 6, 2020

The use of business analytics is a critical component of organizations’ digital transformation initiatives. As big data continues to grow in size and complexity year after year, organizations need to efficiently cut through the massive data volumes they have on hand to find the hidden insights within.

Analytics 52

Analytics Cloud Disaster Recovery Business Analytics 52

Altexsoft

SEPTEMBER 23, 2021

A data hub serves as a single point of access for all data consumers, whether it be an application, a data scientist, or a business user. So, it also allows for managing data for various tasks, providing centralized governance and data flow control capabilities. Data hub architecture.

Architecture 52

Architecture Data Storage IoT 52

Altexsoft

SEPTEMBER 21, 2023

Data in Elasticsearch is organized into documents, which are then categorized into indices for better search efficiency. Each document is a collection of fields, the basic data units to be searched. Fields in these documents are defined and governed by mappings akin to a schema in a relational database.

Weak Development Team 52

Weak Development Team Analytics Engineering Development Team Review 52

Altexsoft

JUNE 20, 2019

Database Management System or DBMS is a software which communicates with the database itself, applications, and user interfaces to obtain and parse data. Also, DBMS comprises the key instruments to govern the database. However, scalability can be a challenge with SQL databases. Scalability challenges. Cons of MySQL.

Systems Review 85

Systems Review System Software Review Open Source 85

Altexsoft

OCTOBER 17, 2019

Low-quality data can also impede and slow down the integration of business intelligence and ML-powered predictive analytics. US company executives that participated in the Data trust pulse survey by PricewaterhouseCoopers noted that unreliable data is one of the obstacles to monetizing data.

Tools 16

Tools Data Technical Advisors Technical Review 16

Agile Engine

DECEMBER 27, 2023

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7. Table of contents 1.

Big Data 52

Big Data Analytics Data Analysis 52

Sunflower Lab

APRIL 2, 2024

By integrating data from fitness trackers and equipment sensors, Power BI helps the fitness center track member progress and adjust programs accordingly. Power Up Your Business Intelligence with Power BI Turn complexity into clarity with our user-friendly Power BI solutions.

Analytics 40

Analytics Machine Learning Artificial Inteligence Analysis 40

Altexsoft

MARCH 30, 2023

To dive deeper into details, read our article Data Lakehouse: Concept, Key Features, and Architecture Layers. The lakehouse platform was founded by the creators of Apache Spark , a processing engine for big data workloads. Besides that, it’s fully compatible with various data ingestion and ETL tools.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Altexsoft

MARCH 14, 2023

In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support. This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. What is a modern data stack?

Data 59

Data Technical Review Software Review Artificial Inteligence 59

Apiumhub

MARCH 4, 2021

With DaaS, organizations can access global data and create benchmarking reports that may include financial performance, turnover, leadership effectiveness with percentile breakdowns. Business intelligence. Companies can offer their data as a service to internal users facilitating business intelligence.

Trends 72

Trends Data Analytics Business Intelligence 72