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. Structured data sources.

Architecture 52

Architecture Data Storage Machine Learning 52

TechCrunch

JANUARY 26, 2022

It plans to use the money to continue investing in its technology stack, to step up with more business development, and to hire more talent for its team, to meet what it believes are changing tides in the world of data warehousing.

Analytics 218

Analytics Data Big Data Business Intelligence 218

CIO

JUNE 6, 2023

On the other hand, a business that needs efficiency to scale may be better served by a central team that provides functions like data governance, platform engineering, architecture, and data engineering to all areas of the business. Heavily regulated industries tend to centralize.

Data 130

Data Analytics Government Culture 130

TechCrunch

FEBRUARY 2, 2022

But, as RudderStack CEO Soumyadeb Mitra argued when I talked to him ahead of today’s announcement, most of the existing customer data pipeline solutions were built for selling to marketing teams, using architectures that make it harder to build the advanced applications that businesses are now looking for.

Data 204

Data Machine Learning Artificial Inteligence Architecture 204

CIO

NOVEMBER 9, 2022

But experienced data analysts and data scientists can be expensive and difficult to find and retain. Self-service analytics typically involves tools that are easy to use and have basic data analytics capabilities. Users have freedom to slice and dice the data without technical know-how,” he says.

Analytics 340

Analytics Metrics Government Business Intelligence 340

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. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

CIO

MARCH 27, 2024

“Le azioni successive per il miglioramento della data quality possono essere sia di processo che applicative e includono la definizione di un modello organizzativo intorno alla data governance , assegnando ruoli e compiti chiari alle varie figure coinvolte (data scientist, data engineering, data owner, data steward, eccetera)”.

ChatGPT 130

ChatGPT Government Artificial Inteligence Business Intelligence 130

TechCrunch

MAY 26, 2022

He’s the founder of Manta , a data lineage platform that automatically scans an organization’s data sources to build a map of data flows. “Data-driven decisions can only be as good as the quality of the underlying data sets and analysis. billion by 2024. ” Kratky said.

Data 228

Data Weak Development Team Enterprise Analysis 228

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

OpenCredo

JULY 13, 2018

The Power of the Architecture-driven Organisation. Project Positron: A Lack of Business Engagement. As an example, imagine Project Positron initiated by its business project sponsor as a modern compute platform for use by other parts of the business. Project Datatron: Architecture-driven Collaboration.

Architecture 40

Architecture Fractional CTO CTO Coach Engineering 40

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

APRIL 16, 2021

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. What is data pipeline. Online Analytical Processing Architecture.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

CIO

FEBRUARY 13, 2023

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). Fleschut says he will also hire more IT personnel this year, especially data scientists, architects, and security and risk professionals.

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Cloudera

OCTOBER 4, 2023

Ability to handle complex analytic queries — especially when we’re using real-time analytics to augment existing business dashboards and reports with large, complex, long-running business intelligence queries typical for those use cases, and not having the real-time dimension slow these down in any way.

Analytics 83

Analytics Machine Learning Artificial Inteligence Telecommunications 83

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes. What have customers been telling us?

Data 89

Data Analytics Open Source Architecture 89

O'Reilly Media - Data

APRIL 3, 2018

Strata Data London will introduce technologies and techniques; showcase use cases; and highlight the importance of ethics, privacy, and security. The growing role of data and machine learning cuts across domains and industries. Many of these data platforms encourage collaboration and sharing of data, features, and models.

Machine Learning 155

Machine Learning Artificial Inteligence Company Case Study 155

Altexsoft

NOVEMBER 28, 2019

But, as a business, you might be interested in extracting value of this information instead of just collecting it. Business intelligence (BI) is a set of technologies and practices to transform business information into actionable reports and visualizations. Who is a business intelligence developer?

Business Intelligence 22

Business Intelligence Technical Review Development Storage 22

KitelyTech

FEBRUARY 3, 2021

Big data and data science are important parts of a business opportunity. Developing business intelligence gives them a distinct advantage in any industry. How companies handle big data and data science is changing so they are beginning to rely on the services of specialized companies.

Big Data 52

Big Data Data Development Business Intelligence 52

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

Lacework

NOVEMBER 1, 2023

This article addresses privacy in the context of hosting data and considers how privacy by design can be incorporated into the data architecture. In many cases we see that customers prefer to have their data stored and managed locally in their home region, both for reasons of regulatory compliance and also business preference.

System Design 52

System Design Systems Review System Data 52

Altexsoft

DECEMBER 9, 2020

We will describe each level from the following perspectives: differences on the operational level; analytics tools companies use to manage and analyze data; business intelligence applications in real life; challenges to overcome and key changes that lead to transition. Data warehouse architecture.

Analytics 102

Analytics Technical Review Technology Applications 102

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

Altexsoft

AUGUST 21, 2019

Dedicated fields of knowledge like data engineering and data science became the gold miners bringing new methods to collect, process, and store data. Using specific tools and practices, businesses implement these methods to generate valuable insights. Data engineer. Data scientists.

Development 44

Development Software Engineering Data Engineering Architecture 44

Datavail

SEPTEMBER 8, 2022

According to an IDG survey , companies now use an average of more than 400 different data sources for their business intelligence and analytics processes. What’s more, 20 percent of these companies are using 1,000 or more sources, far too many to be properly managed by human data engineers.

Data 40

Data Nonprofit Quality Assurance Education 40

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. Who Is an ETL Engineer? Data modeling.

Development 52

Development Storage Recruiting Architecture 52

Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

Agile Engine

DECEMBER 27, 2023

A data analytics consultancy has a team of specialists and engineers who perform data analytics for companies that don’t have the capacity to do it in-house. Predictive analytics, recommendation engines, and AI-driven insights provide businesses with proactive decision support systems, improving accuracy and efficiency.

Big Data 52

Big Data Analytics Data Analysis 52

CIO

APRIL 4, 2023

In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. This architecture is important because, to reap the full benefits of AI, it must be built to scale across an enterprise versus individual AI applications. Constructing the right data architecture cannot be bypassed.

Architecture 130

Architecture Data Analysis Construction 130

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.

Database Administration 64

Database Administration Strategy Data Technical Review 64

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. What is ELT?

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Altexsoft

MARCH 31, 2020

These can be data science teams , data analysts, BI engineers, chief product officers , marketers, or any other specialists that rely on data in their work. The simplest illustration for a data pipeline. Data pipeline components. Data lakes are mostly used by data scientists for machine learning projects.

Data 76

Data Storage Analytics Data Center 76

TIBCO - Connected Intelligence

SEPTEMBER 22, 2020

For today’s most mature enterprise cloud architectures, ultra-quick querying capabilities on petabytes of data is what the modern pace of business demands. And for enterprises running AWS, Amazon Redshift is most certainly a part of the data warehousing picture given its size, flexibility, and scale.

AWS 48

AWS Analytics Cloud Analysis 48

Hu's Place - HitachiVantara

JUNE 5, 2019

You can’t sit back and let some one else make decisions for you about security, data definitions, and business rules and you can’t make these decisions in isolation. Business owners reported immediate benefits from this implementation. Fatima Hamad, Sr.

Technical Review 40

Technical Review Analytics Data Engineering Scalability 40

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

Mobilunity

DECEMBER 28, 2022

Neural networks are composed of interconnected processing nodes called neurons, which can learn to recognize patterns of input data. Business intelligence. Business intelligence involves using data analysis techniques to help businesses make better decisions about their operations and strategies.

Machine Learning 52

Machine Learning Artificial Inteligence Engineering How To 52

O'Reilly Media - Ideas

FEBRUARY 11, 2019

There are many articles that point to the explosion of data, but in order for that data that be useful for analytics and ML, it has to be collected, transported, cleaned, stored, and combined with other data sources. AI and Data technologies in the cloud. Building a Serverless Big Data Application on AWS”.

Big Data 85

Big Data Technology Tools Cloud 85

Altexsoft

SEPTEMBER 20, 2019

Not only technological companies are concerned about data analysis, but any kind of business is. Analyzing business information to facilitate data-driven decision making is what we call business intelligence or BI. How is data visualized in BI? Business intelligence data processing in a nutshell.

Business Intelligence 18

Business Intelligence Tools Data Analytics 18