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.

Architecture 52

Architecture Data Storage Machine Learning 52

Xebia

JANUARY 19, 2023

. – 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. The data engineer is also expected to create agile data architectures that evolve as new trends emerge.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

Sunflower Lab

MARCH 13, 2024

Core Features of Power BI for Supply Chain Analytics From seamless data connectivity to intuitive visualization capabilities and seamless integration with other Microsoft products, Power BI emerges as a vital asset in optimizing supply chain operations.

Transportation 52

Transportation Weak Development Team Metrics Healthcare 52

Protera

SEPTEMBER 13, 2022

Business intelligence managed services are an alternative for enterprisess without the maturity or bandwidth to manage a platform solution. Enterprise managed services are ongoing operational support services delivered by a third-party provider so that companies can stay focused on mission-critical business activities.

Enterprise 52

Enterprise Business Intelligence Cloud Infrastructure 52

Tandem

AUGUST 9, 2023

Disconnect between business and IT, resulting in a lack of data culture Silos often form when people are left to find their own solutions, creating a lack of collaboration and introducing productivity barriers that hinder growth. Data Storage and Management Systems: These systems are used for storing, retrieving, and managing data.

Data 52

Data Culture Analysis Machine Learning 52

Flexagon

MARCH 1, 2022

Enterprises continue to shift to more agile and continuous software development and delivery. What these organizations had in common is that they sought a solution to address their current tech stack and IT landscape while easing adoption of emerging technology and agile processes for faster and more effective continuous delivery.

UI/UX 78

UI/UX DevOps Business Intelligence Azure 78

Cloudera

DECEMBER 10, 2020

Recently, cloud-native data warehouses changed the data warehousing and business intelligence landscape. 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.

Data 98

Data Technical Review Storage Systems Review 98

O'Reilly Media - Data

JULY 23, 2018

Executive Briefing: from Business to AI—missing pieces in becoming "AI ready ". Executive Briefing: Agile for Data Science teams. Over the last few years, many companies have begun rolling out data platforms for business intelligence and business analytics. Temporal data and time-series analytics".

Machine Learning 120

Machine Learning Artificial Inteligence How To Case Study 120

Openxcell

JANUARY 6, 2023

Just a few of the existing cloud services include servers, storage, databases, networking, software, analytics, and business intelligence. Cloud storage functions by allowing users to access and download data on any selected device, such as a laptop, tablet, or smartphone, via an Internet service connection.

Architecture 52

Architecture Cloud Storage Google Cloud 52

Datavail

SEPTEMBER 28, 2022

Data-driven decision making is proving itself to be invaluable in almost every business vertical. The challenge is identifying the right data management/analytics approach that will allow your business to achieve successful data-driven decision making. Increasing business agility: 56%. Data warehouse and analytics.

Data 40

Data Business Intelligence Government Analytics 40

CTOvision

JULY 31, 2013

By Ryan Kamauff Peter Schlampp, the Vice President of Products and Business Development at Platfora, explains what the Hadoop Big Data reservoir is and is not in this webinar that I watched today. Knowing what the HDR is and is not is key to pulling out business intelligence insights and analytics.

Big Data 91

Big Data Data Business Intelligence Analytics 91

CTOvision

FEBRUARY 4, 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. Register here. 7:30 – 8:00 AM.

Fractional CTO 134

Fractional CTO Technical Review Big Data Analytics 134

Actian

MAY 28, 2019

Data is critical to how modern companies operate, from providing actionable analytics and insights to fueling digitally transformed business processes. Most companies use multiple databases to store data at various levels of refinement, from raw source data to highly curated analytics and reports.

Data 40

Data Analytics Machine Learning Artificial Inteligence 40

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

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. Register here. 7:30 – 8:00 AM.

Fractional CTO 113

Fractional CTO Program Management Programming Big Data 113

Altexsoft

APRIL 13, 2023

The annual IHS Markit Supply Chain Survey Report found that 63 percent of companies don’t have sufficient technology to approach their top priority optimization strategy, i.e., spend analytics (the situation within other strategic areas is similar). It also often includes analytics, reporting, and forecasting capabilities.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

OTS Solutions

JUNE 9, 2023

These applications are used to manage and streamline various business processes and operations, including customer relationship management, enterprise resource planning, enterprise resources planning, supply chain management, human resource management, and business intelligence and analytics.

Enterprise 130

Enterprise Applications Development Scalability 130

OTS Solutions

JUNE 9, 2023

These applications are used to manage and streamline various business processes and operations, including customer relationship management, enterprise resource planning, enterprise resources planning, supply chain management, human resource management, and business intelligence and analytics.

Enterprise 130

Enterprise Applications Development Scalability 130

InfoBest

JULY 18, 2018

MongoDB is currently the most popular NoSQL platform and it helps companies like Expedia, Forbes, MetLife or TheGuardian extend their services in areas like the Internet of Things or Business Intelligence. Also, NoSQL has become more and more popular when developing AGILE (quick iterations, no downtime).And CouchDB (Apache).

Engineering 61

Engineering Technical Review PHP Software Review 61

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Altexsoft

MARCH 16, 2023

Modern asset tracking systems allow business operators and managers to always be on top of their assets’ location, condition, maintenance status, and performance, having access to all collected data in centralized storage. make reports, conduct analytics, etc.). So let’s dive deeper into the technicalities.

Technical Review 52

Technical Review Technology Software Review Systems Review 52

Cloudera

SEPTEMBER 23, 2022

The first is near unlimited storage. Leveraging cloud-based object storage frees analytics platforms from any storage constraints. Analytical engines can be scaled up (or down) on demand, as per the requirements of your workload. You will have access to on-demand compute and storage at your discretion.

Government 104

Government Enterprise Strategy Data 104

Cloudera

JANUARY 21, 2021

But – you need those mission critical analytics services, and you need them now! . Waiting in line in the Central IT queue and risk getting behind in your business and losing out to competition as a result? Separate storage. You also do not want to risk your company-wide cloud consumption costs snowballing out of control.

Analytics 93

Analytics Storage Technical Review Virtualization 93

Kaseya

NOVEMBER 9, 2023

With the cloud, users and organizations can access the same files and applications from almost any device since the computing and storage take place on servers in a data center instead of locally on the user device or in-house servers. It enables organizations to operate efficiently without needing any extensive internal infrastructure.

Cloud 105

Cloud Disaster Recovery Artificial Inteligence Infrastructure 105

Cloudera

SEPTEMBER 23, 2022

The first is near unlimited storage. Leveraging cloud-based object storage frees analytics platforms from any storage constraints. Analytical engines can be scaled up (or down) on demand, as per the requirements of your workload. You will have access to on-demand compute and storage at your discretion.

Data 52

Data Storage Analytics Budget 52

Hu's Place - HitachiVantara

APRIL 12, 2018

The key requirements for Data Center Modernization are an agile data infrastructure that is cloud aware and container integrated, data governance which ensures that data is continuously available and adheres to compliance objectives, operation intelligence to provide deeper insights, and automation to optimize and accelerate innovation.

Data Center 40

Data Center Storage Data Compliance 40

Cloudera

OCTOBER 25, 2022

Enabling data and analytics in the cloud allows you to have infinite scale and unlimited possibilities to gain faster insights and make better decisions with data. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses. Vulnerability management.

Cloud 52

Cloud Data Firewall AWS 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

Cloudera

OCTOBER 26, 2017

Become more agile with business intelligence and data analytics. Business intelligence (BI) and analytics in the cloud is an area that has gained the attention of many organizations looking to provide a better user experience for their data analysts and engineers. Clouds (source: Pexels ).

Cloud 42

Cloud Data Storage Analytics 42

Cloudera

DECEMBER 2, 2020

However, it was locked into an expensive legacy data warehouse which resulted in high operational costs and the inability to perform exploratory analytics. With more than 25TB ingested from over 200+ different data sources, Telkomsel knew an agile and cost-efficient infrastructure was key to pursuing a digital-first strategy. .

Data 64

Data Telecommunications Analytics Mobile 64

Protera

MAY 23, 2023

There are several quality cloud providers on the market, but you want to choose the one that best aligns with your unique business requirements and objectives. Other areas of focus to this end could include security, performance efficiency, scalability, and of course cost.

Cloud 52

Cloud Testing Data Center Systems Review 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

DECEMBER 7, 2017

Cloud promises many advantages as an environment for machine learning and analytics. Cloud offers elasticity of those resources to efficiently support transient analytics workloads and data pipelines. Yet there is often a dark side to using public cloud service providers’ analytics offerings in the cloud, too. It’s time for SDX.

Data 40

Data Machine Learning Artificial Inteligence Analytics 40

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. An OLAP or Online Analytical Processing cube is the tool used to represent data for analysis in a multidimensional way.

Data 64

Data Analytics Construction Cloud 64

Cloudera

SEPTEMBER 9, 2018

Businesses need to be agile and quick in using data to drive insights, lest they lose the opportunity they are trying to capitalize on. It’s no surprise that there is a strong correlation between successful businesses and those that exceed in extracting value from data. SDX for Altus for shared data context (data catalog).

Data 40

Data Data Engineering Analytics Cloud 40

CIO

JANUARY 20, 2023

Many companies have been experimenting with advanced analytics and artificial intelligence (AI) to fill this need. Yet many are struggling to move into production because they don’t have the right foundational technologies to support AI and advanced analytics workloads. Some are relying on outmoded legacy hardware systems.

Analytics 329

Analytics Artificial Inteligence Artificial Intelligence Hardware 329

Altexsoft

SEPTEMBER 10, 2021

For example, Amazon receives more than 66,000 orders per hour with each order containing valuable pieces of information for analytics. Yet, dealing with continuously growing volumes of data isn’t the only challenge businesses encounter on the way to better, faster decision-making. The pace of data being created is mind-blowing.

Tools 52

Tools Data Software Review Technical Review 52