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. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

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

Altexsoft

FEBRUARY 8, 2021

For example, you can see that the machine breakdown increased, and the root cause analysis shows that it happened because of cheaper spare parts or fuel. More advanced analytics enable conducting preventive or predictive maintenance based on data from IoT devices and various sensors connected to equipment. Define data sources.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Cloudera

NOVEMBER 28, 2023

Cloudera Private Cloud Data Services is a comprehensive platform that empowers organizations to deliver trusted enterprise data at scale in order to deliver fast, actionable insights and trusted AI. This means you can expect simpler data management and drastically improved productivity for your business users.

Data 84

Data Scalability Analytics Quality Assurance 84

Altexsoft

APRIL 13, 2023

For example, you’ll deal with real-time data streams if you want to adopt predictive maintenance which requires constant condition monitoring or implement an RTLS system to continuously track your handling equipment and other assets. to develop all the data architecture and analytics solutions. Scalability. Data siloes.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Cloudera

DECEMBER 10, 2020

Appealing directly to end-users in the Lines of Business (LOBs), these solutions can dramatically shorten time to value, lower administrative burdens, and promise continuous agility in response to changing business demands. You don’t need a highly skilled administrator to add nodes to the cluster and replicate data to increase capacity.

Data 98

Data Technical Review Storage Systems Review 98

DataRobot

MARCH 16, 2023

To work effectively, data scientists need agility in the form of access to enterprise data, streamlined tooling, and infrastructure that just works. Agility and enterprise security, compliance, and governance are often at odds. They work with partners in IT to harden ML use cases into production systems.

Data 52

Data Machine Learning Artificial Inteligence Agile 52

DataRobot

MARCH 23, 2023

In a challenging economy, agility, speed, and efficiency are vital. Ask further questions to help your organization plan to improve efficiency and agility when working with ML models. Use a cost-benefit analysis to explore ROI and risk. 2 What Is MLOps and How Does It Help? Should You Build or Buy an MLOps Platform?

Artificial Inteligence 52

Artificial Inteligence Machine Learning Weak Development Team Software Review 52

Altexsoft

JULY 19, 2022

This basic principle corresponds to that of agile software development or approaches such as DevOps, Domain-Driven Design, and Microservices: DevOps (development and operations) is a practice that aims at merging development, quality assurance, and operations (deployment and integration) into a single, continuous set of processes.

Architecture 52

Architecture Data Analytics Data Engineering 52

Kentik

JUNE 13, 2016

Detection requires visibility and analysis. Visibility requires information, and analysis requires the ability to contextualize the information. The data is not merely correlated but fully unified to create useful metadata for enhanced context. Reducing a network's intruder dwell time is mostly about detection.

Network 40

Network LAN Big Data Scalability 40

Altexsoft

AUGUST 4, 2021

Data mart vs data warehouse vs data lake architectures. Data marts shouldn’t be confused with OLAP cubes either. An OLAP or Online Analytical Processing cube is the tool used to represent data for analysis in a multidimensional way. For example, a company has a data mart containing all the financial data.

Data 64

Data Analytics Construction Cloud 64

Altexsoft

NOVEMBER 23, 2021

If the transformation step comes after loading (for example, when data is consolidated in a data lake or a data lakehouse ), the process is known as ELT. You can learn more about how such data pipelines are built in our video about data engineering. Popular data virtualization tools.

Virtualization 69

Virtualization Tools Data Architecture 69

Cloudera

OCTOBER 26, 2017

Become more agile with business intelligence and data analytics. Friction associated with getting a data sandbox has also resulted in the proliferation of spreadmarts , unmanaged data marts, or other data extracts used for siloed data analysis. Published originally on O’Reilly.com.

Cloud 43

Cloud Data Storage Analytics 43

CIO

JULY 5, 2023

Around the same time of the release, Repsol appointed Juan José Casado Quintero as its new chief digital officer (CDO), another strategic move to digitally transform and accelerate the company’s strategy to become a data-driven company.

Artificial Inteligence 263

Artificial Inteligence Generative AI Energy Strategic Planning 263

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