Datavail

NOVEMBER 6, 2023

Analytics : DataStax Enterprise incorporates Apache Spark, a powerful analytics engine, into its distribution. This integration enables real-time data processing and complex analytics directly on the Cassandra database, eliminating the need for data movement and reducing latency. x: Corresponding to Apache Cassandra 2.x,

Open Source 58

Open Source Scalability Analytics Database Administration 58

Datavail

DECEMBER 20, 2022

First off, Suyog Pagare, Senior SQL Server Database Administrator, documented his experiences throughout the conference. The platform seamlessly integrates operational databases, analytics, and data governance. Near real-time analytics capabilities. Watch our Video Summary of PASS Data Community Summit.

Data 52

Data Disaster Recovery AWS Azure 52

Datavail

FEBRUARY 2, 2021

MariaDB is an open-source database server created by the original developers of MySQL, and is designed to offer a single complete database that supports analytics, transactional, and hybrid applications. It’s the 12 th most popular database server, according to DB-Engine rankings.

Disaster Recovery 40

Disaster Recovery Data Backup Firewall 40

Perficient

AUGUST 3, 2023

As a result, just like with all SaaS, the need to incorporate Oracle Cloud ERP data into an enterprise data lake house is essential for the success of company-wide data and analytics initiatives. As a columnar database, Oracle ADW is optimized for batch-type querying and data processing.

Cloud 52

Cloud Data Storage Infrastructure 52

Altexsoft

JUNE 20, 2019

Besides active data guard, partitioning, improved backup and recovery, Oracle suggests parallel upgrading to reduce downtime during database upgrades. For example, ClusterControl is a great assistance at managing, monitoring, and scaling SQL and NoSQL open source databases. Strong tech support and documentation. Cons of MSSQL.

Systems Review 85

Systems Review System Software Review Open Source 85

Altexsoft

MAY 12, 2023

It is commonly stored in relational database management systems (DBMSs) such as SQL Server, Oracle, and MySQL, and is managed by data analysts and database administrators. That’s why there must be some sort of data replication, backup strategies, and failover mechanisms. Data security and privacy.

Examples 59

Examples Tools Data Artificial Inteligence 59

Altexsoft

SEPTEMBER 19, 2019

Data sources may be internal (databases, CRM, ERP, CMS, tools like Google Analytics or Excel) or external (order confirmation from suppliers, reviews from social media sites, public dataset repositories, etc.). These BI platforms include ETL and data storage services, along with analytics and reporting with visuals.

Business Intelligence 13

Business Intelligence Tools Data Azure 13

Mobilunity

NOVEMBER 10, 2022

Those could be: Microsoft Technology Associate: Database Fundamentals SQL Certification; Microsoft Certified: Azure Database Administrator Associate. Oracle Database SQL Certified Associate Certification. IBM Certified Database Associate. EDB PostgreSQL 12 Associate Certification.

Development 52

Development How To Comparison Recruiting 52

Openxcell

JANUARY 6, 2023

Instead of making substantial investments in databases, software, and hardware, businesses prefer to access their computing power over the internet or in the cloud. Just a few of the existing cloud services include servers, storage, databases, networking, software, analytics, and business intelligence. There were 2.09

Architecture 52

Architecture Cloud Storage Google Cloud 52

Altexsoft

JULY 4, 2022

Companies often take infrastructure engineers for sysadmins, network designers, or database administrators. They also design and implement a detailed disaster recovery plan to ensure that all infrastructure elements (data and systems) have efficient backup solutions. Infrastructure is quite a broad and abstract concept.

Infrastructure 64

Infrastructure Engineering Technical Review Google Cloud 64

CIO

MARCH 25, 2025

What CIOs can do: Avoid and reduce data debt by incorporating data governance and analytics responsibilities in agile data teams , implementing data observability , and developing data quality metrics. For this reason, organizations with significant data debt may find pursuing many gen AI opportunities more challenging and risky.

Technical Review 210

Technical Review Weak Development Team Software Review Database Administration 210