CIO

JULY 26, 2023

We made a commitment to be truly cloud native and build an architecture that wasn’t burdened by any legacy infrastructure,” says Cox. The Denver-based realty chain has also developed a homegrown Salesforce-based business intelligence app running off Tableau to power its global network of roughly 145,000 brokers and agents, Ligon says.

Real Estate 244

Real Estate Data Generative AI Machine Learning 244

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

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Many companies are just beginning to address the interplay between their suite of AI, big data, and cloud technologies. I’ll also highlight some interesting uses cases and applications of data, analytics, and machine learning. Data Integration and Data Pipelines. Automation in data science and big data.

Big Data 87

Big Data Technology Tools Cloud 87

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 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

CTOvision

JULY 9, 2014

The term “Big Data” has become synonymous with this evolution. But still, many of our customers continue to ask, “What is Big Data?”, “What are its use cases?”, and “What is its business value?”. What is Big Data? To gain value from this data, you must choose an alternative way to process it.”

Big Data 114

Big Data Data CTO Fractional CTO 114

TechCrunch

SEPTEMBER 29, 2022

Petrossian met Coalesce’s other co-founder, Satish Jayanthi, at WhereScape, where the two were responsible for solving data warehouse problems for large organizations. (In In computing, a “data warehouse” refers to systems used for reporting and data analysis — analysis usually germane to business intelligence.)

Enterprise 184

Enterprise Data Business Intelligence Analytics 184

CTOvision

SEPTEMBER 11, 2016

Their solutions have served business users, including the more advanced statisticians and data scientists but also the average user. We track Tibco in our Disruptive IT Directory in the category of Business Intelligence and Analytics Companies.

Business Intelligence 60

Business Intelligence Analytics Telecommunications Airlines 60

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

CIO

MARCH 24, 2023

A framework for managing data 10 master data management certifications that will pay off Big Data, Data and Information Security, Data Integration, Data Management, Data Mining, Data Science, IT Governance, IT Governance Frameworks, Master Data Management

Government 357

Government Data Technical Review Policies 357

CIO

MARCH 27, 2024

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

ChatGPT 130

ChatGPT Government Artificial Inteligence Business Intelligence 130

CTOvision

SEPTEMBER 11, 2016

The result of Tibco's acquisitions and their own foundation of BI tools is a company that can integrate apps, enhance business process management, improve master data management, enable complex event and in stream processing, and visualize data holdings.

Business Intelligence 62

Business Intelligence Analytics Telecommunications Airlines 62

Altexsoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data 87

Data Data Engineering Big Data Architecture 87

Kentik

MAY 31, 2016

In the first post we discussed the need for a Big Data approach to network management in order to support agile business models and rapid innovation. In the second post we looked at how insights from a Big Data approach to network management enable data-driven network operations. trillion dollar problem.

Big Data 40

Big Data Data Analytics Weak Development Team 40

CTOvision

MARCH 14, 2014

But seeing financial results reported like the below just underscores that this is the right firm to leverage for your data integration needs. Pentaho Announces Record Year in 2013 with 83% Growth in Big Data and Embedded Analytics. The introduction of Pentaho Business Analytics 5.0 Download the full report.

Big Data 107

Big Data Business Analytics Analytics Business Intelligence 107

Altexsoft

APRIL 22, 2020

In its core, data science is all about getting data for analysis to produce meaningful and useful insights. The data can be further applied to provide value for machine learning , data stream analysis , business intelligence , or any other type of analytics. We need to store extracted data somewhere.

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

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

Altexsoft

OCTOBER 24, 2019

We will define how enterprise warehouses are different from the usual ones, what types of data warehouses exist, and how they work. The focus of this material is to provide information about the business value of each architectural and conceptual approach to building a warehouse. What is an Enterprise Data Warehouse?

Architecture 50

Architecture Enterprise Data Technical Review 50

Apiumhub

APRIL 6, 2021

You will often learn some new concepts and actionable tips to enhance your data science and machine learning skills. Data Science Central Data Science Central acts as an online resource hub for just about everything related to data science and big data.

Technical Review 52

Technical Review Data Artificial Inteligence Software Review 52

Altexsoft

DECEMBER 9, 2020

Moreover, the MicroStrategy Global Analytics Study reports that access to data is extremely limited, taking 60 percent of employees hours or even days to get the information they need. Diagnostic analytics identifies patterns and dependencies in available data, explaining why something happened. Analytics maturity model.

Analytics 102

Analytics Technical Review Technology Applications 102

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

Kentik

FEBRUARY 14, 2023

In today’s digital world, data is generated faster and at a larger scale than ever before. With software architectures increasingly adopting distributed, cloud-based models , network infrastructures have become complex webs of virtual and physical devices. What are the main features of a modern data platform?

Network 52

Network Data Artificial Inteligence Analysis 52

Perficient

FEBRUARY 28, 2023

This included: First understanding and prioritizing the business and IT needs and challenges Defining the platform and program architecture, AND selecting the cloud platform and tools, And defining the program structure, project organization, and execution plan to implement the roadmap.

Healthcare 64

Healthcare Technical Review AWS Analytics 64

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

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 93

Data Analytics Storage Big Data 93

Perficient

FEBRUARY 13, 2023

Through past implementations, Perficient has learned a lot about what adds time, effort, and cost to healthcare data & analytics projects. The Lakehouse also includes design patterns to enable data tenancy tags to be applied and managed within the Lake and Publish layers.

Healthcare 64

Healthcare AWS Analytics Pharmaceuticals 64

CTOvision

JANUARY 19, 2014

I reviewed a years worth of reporting at CTOvision.com, FederalTimes, SiliconANGLE, Mashable and TechCrunch with an eye to the technology stories I believe had the biggest impact on the federal enterprise in 2013. 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

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

Altexsoft

JANUARY 14, 2021

We’ll review all the important aspects of their architecture, deployment, and performance so you can make an informed decision. Before jumping into the comparison of available products right away, it will be a good idea to get acquainted with the data warehousing basics first. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

DECEMBER 17, 2019

In the business sphere, a certain area of technology aims at helping people make the right decisions, by supporting them with the right data. This field is called business intelligence or BI. What is SAP Business Intelligence? Database and data management solutions. SAP Business Intelligence.

Business Intelligence 19

Business Intelligence Weak Development Team Systems Review Software Review 19

Mobilunity

MARCH 26, 2024

SAP NetWeaver Business Warehouse (BW): As a matter of fact this component does not only change raw data into meaningful insights but it also serves as a hub where data from multiple sources can be consolidated thus providing an inclusive business intelligence and reporting platform.

Project Management 52

Project Management Recruiting Agile Quality Assurance 52

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

Mobilunity

NOVEMBER 24, 2021

The demand for specialists who know how to process and structure data is growing exponentially. In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. Data modeling. Who Is an ETL Engineer?

Development 52

Development Storage Recruiting Architecture 52

Gorilla Logic

MAY 19, 2021

KPMG reports that 67 percent of tech leaders struggle to find the right tech talent, and 22 percent of organizations surveyed by Coding Sans ranked increasing development capacity as their top challenge. Some of the most common include cloud, IoT, big data, AI/ML, mobile, and more. Cloud capabilities for software outsourcing.

Software Review 94

Software Review Technical Review Software Development Team Review 94

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. within a single, centralized location for analytics and reporting.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

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

OCTOBER 30, 2021

The movement of data from its source to analytical tools for end users requires a whole infrastructure, and although this flow of data must be automated, building and maintaining it is a task of a data engineer. Data engineers are programmers that create software solutions with big data. Programming.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98