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

Agile Engine

DECEMBER 27, 2023

Introduction With the growing availability of cloud and AI, the data collected by organizations is now worth its weight in gold. Large-scale, granular, and actionable data analytics is more accessible than ever, but it still comes with numerous challenges. That’s where data analytics consultancies come into play.

Big Data 52

Big Data Analytics Data Analysis 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. How data engineering works in 14 minutes. Source: Databricks.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Lacework

NOVEMBER 1, 2023

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. A mart is a group of aggregated tables (e.g., 1 [link] 2 [link] 3 [link] 4 [link] 5 [link] 6 [link] 7 [link]

System Design 52

System Design Systems Review System Data 52

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 and is not.

Architecture 52

Architecture Data Analytics Data Engineering 52

Cloudera

OCTOBER 25, 2022

“They combine the best of both worlds: flexibility, cost effectiveness of data lakes and performance, and reliability of data warehouses.”. It allows users to rapidly ingest data and run self-service analytics and machine learning. Compliance monitoring and incident response.

Cloud 52

Cloud Data Firewall AWS 52

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

Capgemini

NOVEMBER 14, 2022

Data has to be easy to find, understand, access, and use for everyone in the chain: data engineers, analysts, data scientists, and business users. It makes the data more accessible and understandable to everyone, especially less-skilled data consumers. A data catalog for trust. Myles Suer.

Agile 52

Agile Technical Review Systems Review Artificial Intelligence 52

Altexsoft

MARCH 14, 2023

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. Data democratization.

Data 59

Data Technical Review Software Review Artificial Inteligence 59

Altexsoft

NOVEMBER 9, 2021

Manual operations and/or outdated technology aren’t able to provide the required visibility and support your decisions. It’s usually used to adjust existing predictions within fast-changing markets such as innovative technology. Accurate forecasting is a foundation of intelligent planning and budgeting. Compliance evaluation.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Altexsoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Let’s elaborate on this and figure out how a data lakehouse is different from its ancestors and name inspirers in more detail. Data warehouse.

Architecture 52

Architecture Data Storage Machine Learning 52

Cloudera

DECEMBER 7, 2017

Cloud service providers now offer a plethora of “house brand” analytics services, some brand new, some re-purposed versions of older technologies. As each new service is started, data is typically copied in for analysis. That data may be used in ways that don’t comply with appropriate security and governance policies.

Data 40

Data Machine Learning Artificial Inteligence Analytics 40

Cloudera

AUGUST 31, 2021

Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis. Conclusion.

Data 82

Data Analytics Cloud Technical Review 82

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. Is it still so? Quite the opposite.

Backup 115

Backup Azure Software Review Systems Review 115

Datavail

MARCH 10, 2022

Data stewards – provide oversight of data sets to maintain data integrity and ensure implementation of policies from the committee and end-user compliance with the policies. Others – data modelers, data engineers, data architects, and data quality analysts also contribute to the DG process.

Government 40

Government Strategy Weak Development Team Company 40

Cloudera

DECEMBER 10, 2020

Some data warehousing solutions such as appliances and engineered systems have attempted to overcome these problems, but with limited success. . Recently, cloud-native data warehouses changed the data warehousing and business intelligence landscape. What makes CDW unique and cost attractive?

Data 98

Data Technical Review Storage Systems Review 98

Altexsoft

SEPTEMBER 9, 2022

Metadata management is a set of activities, technologies, and policies that target metadata collection, storage, and organizing. It aims at making data assets understandable and discoverable for users. Efficient metadata management ensures data integrity , consistency, trustworthiness, and compliance. Data governance.

Tools 59

Tools Technical Review Software Review Systems Review 59

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 350

Data Artificial Inteligence Technical Advisors Technical Review 350

TIBCO - Connected Intelligence

DECEMBER 20, 2021

TIBCO DQ will become the new data quality product family, through an evolution of our current data quality offerings, significantly enhancing current capabilities available throughout the TIBCO data fabric with built-in AI and ML to automate quality, detection, monitoring, and anomaly resolution.

Innovation 26

Innovation Analytics Virtualization Cloud 26

Abhishek Tiwari

JULY 20, 2019

As Steve Jobs wisely said, Don’t Be Trapped by Dogma – Which is Living With the Results of Other People’s Thinking In my view, technology executives and engineering leaders are overly obsessed with the Spotify model. Specialisation could be around products, business process, or technologies. And there lies the problem.

Engineering 61

Engineering Weak Development Team Software Review Technical Review 61