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

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

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

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. Data Platforms. Data Integration and Data Pipelines. AI and Data technologies in the cloud.

Big Data 87

Big Data Technology Tools Cloud 87

Hu's Place - HitachiVantara

JUNE 5, 2019

” In the last half of last year we applied DataOps to consolidate our enterprise reporting systems into one data lake. 32 data domain owners from governance, pricing, services, procurement, partners, sales, marketing, supply planning and IT were involved. We know it works because we use DataOps in our own operations.”

Technical Review 40

Technical Review Analytics Data Engineering Scalability 40

Altexsoft

SEPTEMBER 9, 2022

Metadata management is a part of the data governance process which, in turn, is an element of the overall data management strategy. Today, such modern data management frameworks as DataOps strongly rely on effective metadata capture and management to bring order into the chaotic data flows. data cataloging).

Tools 59

Tools Technical Review Software Review Systems Review 59

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. You have a centralized data catalog and schema registry.

Data 98

Data Technical Review Storage Systems Review 98

Cloudera

AUGUST 30, 2022

Data is the fuel that drives government, enables transparency, and powers citizen services. Citizens who have negative experiences with government services are less likely to use those services in the future. Modern data architectures. Deploying modern data architectures. Forrester ).

Architecture 79

Architecture Data Artificial Inteligence Artificial Intelligence 79

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.

Data 84

Data Analytics Cloud Technical Review 84

Altexsoft

JULY 19, 2022

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. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two. What data mesh IS.

Architecture 52

Architecture Data Analytics Data Engineering 52

CIO

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). You can intuitively query the data from the data lake.

Data 350

Data Artificial Inteligence Technical Advisors Technical Review 350

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

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

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Why integrate Apache Iceberg with Cloudera Data Platform?

Data 87

Data Analytics Machine Learning Artificial Inteligence 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

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

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

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 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. Specialist responsible for the area: data governance analyst.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

JULY 29, 2022

According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Apache Hadoop architecture. What happens, when a data scientist, BI developer , or data engineer feeds a huge file to Hadoop?

Big Data 59

Big Data Data Google Cloud Storage 59

Cloudera

DECEMBER 7, 2017

That data may be stored multiple times in different pools, each multiplying storage resource costs. That data may be used in ways that don’t comply with appropriate security and governance policies. That data may be hard to discover for other users and other applications.

Data 40

Data Machine Learning Artificial Inteligence Analytics 40

Cloudera

NOVEMBER 2, 2020

On the technical side, it is cheaper and easier than ever to instrument everything and send that data in real-time through a messaging system. On the business side, companies and governments are digitizing and automating as many of their operations as possible so decision making and asset management can be more effective.

Data 95

Data Analytics Storage Big Data 95

Cloudera

OCTOBER 26, 2017

Become more agile with business intelligence and data analytics. Many of us are all too familiar with the traditional way enterprises operate when it comes to on-premises data warehousing and data marts: the enterprise data warehouse (EDW) is often the center of the universe. Clouds (source: Pexels ).

Cloud 43

Cloud Data Storage Analytics 43

Altexsoft

OCTOBER 8, 2021

As such, you can bridge the differences between data models of source systems and destinations by matching data fields and defining data transfer frequency. Last but not least, all vendors present customers with the capability of secure data integration operations. Snaplogic iPaaS architecture. Source: G2.

Tools 52

Tools Data Software Review Open Source 52

Altexsoft

NOVEMBER 9, 2021

You can request quotes from various vendors and then compare them side-by-side, as well as to related market prices, Federal Government established prices, historical prices, and so on. formatting, content, security, archiving, connections with government institutions, and so on. Extract data. Consolidate data.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Altexsoft

OCTOBER 3, 2019

Deloitte reports that The Ministry of Energy of the Government of Mexico uses a predictive workforce planning and analytics model to learn about the current shortage of skilled workers in the oil and gas industry and predict one over a 10-year horizon. Data engineer builds interfaces and infrastructure to enable access to data.

Analytics 16

Analytics Company Off-The-Shelf How To 16

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

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. Data augmentation 
We’ll bring you a 360-degree view of the customer landscape by augmenting assets with third-party data and predictive analytics.

Big Data 52

Big Data Analytics Data Analysis 52

Altexsoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

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. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it.

Data 59

Data Technical Review Software Review Artificial Inteligence 59