CIO

FEBRUARY 13, 2023

Fifty-two percent of organizations plan to increase or maintain their IT spending this year, according to Enterprise Strategy Group. This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%).

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Altexsoft

FEBRUARY 11, 2023

Data architect and other data science roles compared Data architect vs data engineer Data engineer is an IT specialist that develops, tests, and maintains data pipelines to bring together data from various sources and make it available for data scientists and other specialists.

Data 87

Data Data Engineering Big Data Architecture 87

Altexsoft

JUNE 29, 2021

MLEs are usually a part of a data science team which includes data engineers , data architects, data and business analysts, and data scientists. Who does what in a data science team. Machine learning engineers are relatively new to data-driven companies.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Datavail

JUNE 20, 2023

Percona Live 2023 was an exciting open-source database event that brought together industry experts, database administrators, data engineers, and IT leadership. 93% of large enterprises use database monitoring and management solutions. 32% of large enterprise database deployments use Database-as-a-Service offerings.

Open Source 52

Open Source Database Administration Survey AWS 52

Mobilunity

MAY 8, 2023

An Enterprise Data Lake is a large, centralized repository that stores structured and unstructured data at scale. It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise.

Engineering 52

Engineering Data Storage AWS 52

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. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

Capgemini

JANUARY 17, 2023

For the second year in a row, Databricks recently partnered with MIT Technology Review Insights to survey 600 CIOs, CTOs, and CDOs from large enterprises. The key result: CxOs and boards recognize that their organizations’ ability to generate actionable insights from data, often in real-time, is of the highest strategic importance.

Strategy 52

Strategy Technical Review Data Artificial Inteligence 52

Cloudera

JUNE 7, 2022

Sure we can help you secure, manage, and analyze PetaBytes of structured and unstructured data. We do that on-prem with almost 1 ZB of data under management – nearly 20% of that global total. We can also do it with your preferred cloud – AWS, Azure or GCP. Don’t just take our word for it, look at the stats.

Data 106

Data Architecture Analytics Government 106

ParkMyCloud

JANUARY 17, 2020

Each of the ‘big three’ cloud providers (AWS, Azure, GCP) offer a number of cloud certification options that individuals can get to validate their cloud knowledge and skill set, while helping them advance in their careers and broaden the scope of their achievements. . Microsoft Azure Certifications.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

O'Reilly Media - Ideas

JUNE 4, 2019

Spotlight on Data: Data Storytelling with Mico Yuk , July 15. Product Management for Enterprise Software , July 18. Programming with Data: Advanced Python and Pandas , July 9. Understanding Data Science Algorithms in R: Regression , July 12. Cleaning Data at Scale , July 15. Why Smart Leaders Fail , July 16.

Course 64

Course Training Artificial Inteligence Software Review 64

O'Reilly Media - Ideas

JUNE 5, 2019

Spotlight on Data: Data Storytelling with Mico Yuk , July 15. Product Management for Enterprise Software , July 18. Programming with Data: Advanced Python and Pandas , July 9. Understanding Data Science Algorithms in R: Regression , July 12. Cleaning Data at Scale , July 15. Why Smart Leaders Fail , July 16.

Course 49

Course Training Artificial Inteligence Software Review 49

Datavail

JUNE 8, 2023

From DBA to Data Engineer—The Strategic Role of DBAs in the Cloud Over the past few years, the IT landscape has experienced significant disruptions. Additionally, emerging data types and modern applications drive enterprises to adopt new data platforms. Plus, we gave away an awesome LEGO NASA Space Shuttle!

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

Altexsoft

JANUARY 14, 2021

A data warehouse is defined as a centralized repository where a company stores all valuable data assets integrated from different channels like databases, flat files, applications, CRM systems, etc. A data warehouse is often abbreviated as DW or DWH. You may also find it under the name of an enterprise data warehouse (EDW).

Backup 115

Backup Azure Software Review Systems Review 115

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Performance and scalability. Read why the future of data lakehouses is open.

Cloud 76

Cloud Data Analytics Machine Learning 76

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview.

Analytics 20

Analytics Data IoT Analysis 20

Altexsoft

DECEMBER 4, 2020

Here, we’ll focus on tools that can save you the lion’s share of tedious tasks — namely, key types of data migration software, selection criteria, and some popular options available in the market. Types of data migration tools. There are three major types of data migration software to choose from. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

Cloudera

SEPTEMBER 28, 2021

Cloudera Data platform ( CDP ) provides a Shared Data Experience ( SDX ) for centralized data access control and audit in the Enterprise Data Cloud. The procedure to onboard CDP users and groups for AWS cloud storage with an example for a data scientist (DS) and data engineering (DE) group is documented here. .

Groups 61

Groups Cloud AWS Data 61

Palo Alto Networks

AUGUST 23, 2021

Together, they address the unique requirements of both cloud security teams requiring DevOps speed and SOC analysts requiring visibility across their entire enterprise. Cortex XDR’s Third-Party Data Engine Now Delivers the Ability to Ingest, Normalize, Correlate, Query and Analyze Data from Virtually Any Source.

Cloud 89

Cloud Machine Learning Artificial Inteligence Analytics 89

Kentik

MARCH 7, 2023

So far in this series , I’ve outlined how a scaling enterprise’s accumulation of data (data gravity) struggles against three consistent forces: cost, performance, and reliability. Despite what was supposed to be a robust and expansive series of ExpressRoutes with Azure, the retailer’s system kept experiencing cascading failures.

Network 99

Network Cloud Data Case Study 99

Altexsoft

APRIL 26, 2022

With the consistent rise in data volume, variety, and velocity, organizations started seeking special solutions to store and process the information tsunami. This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance. CRMs, OLAP/OLTP databases, enterprise applications, etc.)

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Cloudera

SEPTEMBER 9, 2018

It enables organizations to address their data warehousing reporting needs by making it quick and easy to consolidate data into a single repository yet still service your users’ needs in a scalable and cost-effective way. This makes it easy to meet the ever-changing needs of your data teams.

Data 40

Data Data Engineering Analytics Cloud 40

Altexsoft

JULY 19, 2022

Through all these shifts, data mesh is called to solve the problems of centralized data platforms by giving more flexibility and independence, agility and scalability, cost-effectiveness, and cross-functionality. Data mesh principles and architecture. And it’s their job to guarantee data quality.

Architecture 52

Architecture Data Analytics Data Engineering 52

O'Reilly Media - Ideas

MARCH 1, 2023

Decomposing a complex monolith into a complex set of microservices is a challenging task and certainly one that can’t be underestimated: developers are trading one kind of complexity for another in the hope of achieving increased flexibility and scalability long-term. Data engineering was the dominant topic by far, growing 35% year over year.

Trends 133

Trends Technical Review Technology Software Review 133

Altexsoft

OCTOBER 8, 2021

This often includes such procedures as data profiling (searching for errors and inconsistencies), cleansing (removing duplicates, corrupted items, etc.), Data integration process. On the enterprise level, data integration may cover a wider array of data management tasks including. high security. Source: Oracle.

Tools 52

Tools Data Software Review Open Source 52

Altexsoft

OCTOBER 2, 2020

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. Fitting into wider enterprise architecture, it outlines how data is collected, integrated, transformed, stored, and used.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. Still, it’s the number one choice for data-driven companies, and here’re some reasons why. Scalability.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

NOVEMBER 5, 2021

A more advanced version is the enterprise Master Patient Index (eMPI) that brings together patient documents stored in multiple sources and thus facilitates cross-system information sharing. Patient identity management with Enterprise Master Patient Index. If so, the MPI assigns them the same enterprise identifier.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Cloudera

OCTOBER 26, 2017

Check out Greg Rahn’s session, “ Rethinking data marts in the cloud: Common architectural patterns for analytics ” at the Strata Data Conference in Singapore, December 4-7, 2017, to learn how to architect analytic workloads in the cloud and the core elements of data governance. Let’s discuss each in more detail.

Cloud 42

Cloud Data Storage Analytics 42

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. Similar to some cloud data warehouses , the lakehouse architecture implies the use of separate clusters for storage and compute.

Architecture 52

Architecture Data Storage Machine Learning 52

Cloudera

FEBRUARY 14, 2022

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. Each unlocking value in the data engineering workflows enterprises can start taking advantage of.

Data Engineering 109

Data Engineering Engineering Data Storage 109

Altexsoft

MARCH 30, 2023

But what do the gas and oil corporation, the computer software giant, the luxury fashion house, the top outdoor brand, and the multinational pharmaceutical enterprise have in common? The answer is simple: They use the same technology to make the most of data. How data engineering works in 14 minutes.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Cloudera

MAY 18, 2021

Infrastructure cost optimization by enabling container-based scalability for compute resources based on processing load and by leveraging object storage that has lower price point than compute-attached storage. Experience configuration / use case deployment: At the data lifecycle experience level (e.g., 1 Year Reserved . 13,000-18,500.

Cloud 83

Cloud Technical Review Storage Backup 83

Cloudera

FEBRUARY 22, 2021

Those ancillary tools provide “must-have” capabilities for enterprise-grade deployments, such as fine-grained access control, workload observability, data abstraction and data discovery. AWS, Google or Azure) and thus allow for execution of a use case wherever it is most costs effective to do so.

Data 76

Data Analytics Government Technical Review 76