Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Deploying modern data architectures. Lack of sharing hinders the elimination of fraud, waste, and abuse. Forrester ).

Architecture 78

Architecture Data Artificial Inteligence Artificial Intelligence 78

CIO

AUGUST 18, 2022

To find out, he queried Walgreens’ data lakehouse, implemented with Databricks technology on Microsoft Azure. “We For Guadagno, the need to match vaccine availability with patient demand came at the right moment, technologically speaking. Enter the data lakehouse. You can intuitively query the data from the data lake.

Data 349

Data Artificial Inteligence Technical Advisors Technical Review 349

Altexsoft

JULY 19, 2022

No matter how ridiculous it may sound, the famous quote is applicable to the technology world in many ways. In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. What data mesh IS.

Architecture 52

Architecture Data Analytics Data Engineering 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. Different technologies and methods are used and different specialists are involved. Often, no technologies are involved in data analysis.

Analytics 102

Analytics Technical Review Technology Applications 102

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. We change the discussion from one of scale to one of speed and efficiency.”.

Analytics 218

Analytics Data Big Data Business Intelligence 218

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

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

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? Data warehouse vs data lake vs data lakehouse: What’s the difference. Data warehouse.

Architecture 52

Architecture Data Storage Machine Learning 52

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

FEBRUARY 13, 2023

The economy may be looking uncertain, but technology continues to drive the business and CIOs are investing big in 2023. At the same time, they are defunding technologies that no longer contribute to business strategy or growth.

Budget 363

Budget Artificial Inteligence Technical Review VR 363

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. Image Credits: Manta. billion by 2024. ” Kratky said.

Data 228

Data Weak Development Team Enterprise Analysis 228

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. “It Users have freedom to slice and dice the data without technical know-how,” he says.

Analytics 336

Analytics Metrics Government Business Intelligence 336

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Highlights and use cases from companies that are building the technologies needed to sustain their use of analytics and machine learning. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Temporal data and time-series analytics.

Big Data 87

Big Data Technology Tools Cloud 87

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

MARCH 30, 2023

The answer is simple: They use the same technology to make the most of data. Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions. Databricks lakehouse platform architecture. Delta Lake integrations.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

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

Altexsoft

APRIL 16, 2021

In this article, we’ll talk about such a solution —- Online Analytical Processing , or OLAP technology. Namely, we’ll explain what functions it can perform, and how to use it for data analysis. An overview of data warehouse types. What is data pipeline. OLTP vs OLAP: technology comparison. Data operations in OLAP.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

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. Data Science and Machine Learning sessions will cover tools, techniques, and case studies.

Machine Learning 154

Machine Learning Artificial Inteligence Company Case Study 154

Altexsoft

FEBRUARY 22, 2022

Technological solutions to fleet maintenance. To support your preventive maintenance strategy, you have two technological options. Integration with a business intelligence tool is important to receive a holistic analysis of your maintenance processes, track costs, visualize trends, and get actionable insights.

Software Review 52

Software Review Technical Review Software Technology 52

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

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

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. Modern data pipeline with Snowflake technology as its part.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

JANUARY 14, 2021

From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. For over 30 years, data warehouses have been a rich business-insights source. 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

TechCrunch

APRIL 13, 2021

.” And businesses want this very granular data to be reflected inside of their data warehouses, Brown noted, but he also stressed that Meroxa can expose this stream of data as an API endpoint or point it to a Webhook.

Data 248

Data Software Engineering Open Source Engineering 248

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

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. How data engineering works in a nutshell.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

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

Altexsoft

JULY 29, 2022

The biggest star of the Big Data world, Hadoop was named after a yellow stuffed elephant that belonged to the 2-year son of computer scientist Doug Cutting. The toy became the official logo of the technology, used by the major Internet players — such as Twitter, LinkedIn, eBay, and Amazon. Apache Hadoop architecture.

Big Data 59

Big Data Data Google Cloud Storage 59

Altexsoft

MARCH 18, 2021

It is the process of collecting raw data from disparate sources, transmitting it to a staging database for conversion, and loading prepared data into a unified destination system. As data keeps growing in volumes and types, the use of ETL becomes quite ineffective, costly, and time-consuming. Technology maturity.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

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. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

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. Data security: preventing data breaches.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

OCTOBER 21, 2022

Kafka can continue the list of brand names that became generic terms for the entire type of technology. Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. Kafka architecture. If only Jay had different tastes.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

O'Reilly Media - Ideas

FEBRUARY 11, 2020

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. An additional 7% are data engineers.

Weak Development Team 129

Weak Development Team Data Technical Review Survey 129

Altexsoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. A Modern Data Stack (MDS) is a collection of tools and technologies used to gather, store, process, and analyze data in a scalable, efficient, and cost-effective way.

Data 59

Data Technical Review Software Review Artificial Inteligence 59

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