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Trends and Applications
We all know that in uncertain times, a forecast underlies a company's success or failure. Forecasts keep prices low by optimizing business operations—including cash flow, production, staff, and financial management—while increasing knowledge of the market. Business forecasting gives you an essential tool for adapting to change and fostering competitive advantage.But relevant forecasting isn't easy.
Over the last few years it has been fascinating to see how organizations evolve their data management and application development environments. Traditionally, companies depended on monolithic architectures that initially served them well, however today's on-demand business environment calls for a model that can support a more flexible, microservices-driven approach, and facilitate the pace of innovation. Why is this trend towards microservices and a DevOps approach becoming so pervasive? The answer relates to a higher-level trend: the push towards on-demand IT, as the focus has shifted to prioritize the developer experience, and the specific technologies they are using.
To meet the needs of the digital economy of the 2020s, data architecture has evolved into a different animal than it was 10, or even 5, years ago. Most notably, there are three trends that have changed the way enterprises look at and design their data architectures.
Let's start by admitting that the title of this article is a tease. It's a valid question and one that thinking people ask all the time. But in truth it's not the first question you should be asking. More importantly, the answer to the question really depends on how you answer the questions that you should be asking first. Here the questions to ask.
One of the challenges of working with Hadoop environments has been maintaining the infrastructure for big data projects. That's where cloud makes things easier and, increasingly, has served as the underlying infrastructure platform of choice for Hadoop initiatives. At the same time, not everything has moved to the cloud just yet for big data environments. Many IT managers expect to live in a hybrid environment. They are planning for multi-cloud data management to deliver business value and are also still relying on old-school approaches and manual tools to support their data environments.
Columns - Database Elaborations
The meaning and interrelationships of and between data are important. If you are the designer of a database and being lobbied to allow the creation of a table without a primary key, make sure you understand how the table is to be used, and that people will not be writing queries against the structure that will potentially be multiplying data unexpectedly
Columns - DBA Corner
If you've been paying attention at all, I'm sure you've heard the term "phishing." It is used to describe the fraudulent practice of sending emails purporting to be from a reputable source to induce individuals to reveal personal information, such as passwords and credit card numbers. But maybe you haven't heard the term "vishing" yet.
Columns - Quest IOUG Database & Technology Insights
One of the major drivers behind auditing is regulatory compliance. In addition, there are many internal rules and regulations mandated by companies themselves, as well as other reasons for auditing, including monitoring and analyzing database activities for malicious and abnormal activities, developing threat detection with real-time monitoring, and integration with SIEM (security information and event management) solutions for analysis.
Columns - Next-Gen Data Management
The global pandemic has forced companies to pivot over the past year in significant ways. Whether it was transitioning to a remote workforce or reimagining how to interact with customers, digital transformation initiatives within businesses were happening tenfold. As part of that, the pandemic notably accelerated corporate planning for cloud computing.
Columns - Emerging Technologies
In the last 5 years, we've seen a blurring of the distinction between many of the upstart databases and the traditional SQL databases. NoSQL databases such as MongoDB have added features typically associated with relational databases—transactions, SQL connectors, and the like—while the SQL databases have introduced support for JSON document models. We can see that databases such as PostgreSQL and MongoDB are increasingly converging on a common set of features. However, one category of NoSQL databases seems to be bucking the convergence trend: graph databases.
BlueFinity is updating its Evoke low-code app development platform with an integrated and adaptable 360-degree imaging virtual tour capability. This is a multi-purpose feature that provides for the searching, browsing and inspection of any store, venue, property, or utility through an integrated feature of an app. According to the company, the results are sophisticated, full-function web and mobile apps that can be fully integrated with any database (Db2, SQL, Oracle, MultiValue, etc.).
Kore is enhancing its flagship MV platform with performance updates and capabilities that that make RESTful integration, application integration, and data warehousing projects faster and easier to complete.
Rocket Software is gearing up to release the Rocket MultiValue Performance Experience (MVX: P), a system monitoring tool for Rocket UniVerse enabling users to understand and enhance UniVerse performance. Simply put, MVX: P helps users identify and escalate performance-impacting events. Escalated events include possible resolutions and a snapshot of contextually relevant data captured when the event triggered, allowing users to easily track the source of the issue and address it.