As the metaverse unfolds and more and more companies are looking to join the fray we are seeing the progression of development life cycles of various hardware and software.
Virtual reality headsets are getting smaller, faster, wireless, and more portable than ever before. As the hardware advances, we are also seeing a seamless transition on the software side to OpenXR.
The Future of Virtual Reality
As headsets evolve, the likes of Quest 1 & 2 and the upcoming project Cambria will all look to build upon the OpenXR standard framework. The multi-billion-dollar wager on the future of XR tech by Meta proves that this industry is here to stay — hence standards need to be set and built upon for cross-platform redundancy. In a virtual roundtable discussion with reporters, Meta’s own Mark Zuckerberg announced the latest in a series of prototypes that will be paving the way for the future of XR.
Meta is looking to innovate in massive ways as it looks towards a consumer-based future in the metaverse where users will bask in full XR glory for media consumption, shopping, entertainment, and more. While this will unfold over the next decade or so, the reality is that we are in the very early days of both augmented and virtual reality technology and will continue to see incremental improvements over time.
The Holocake 2 prototype
Other hardware suppliers like Pico and HTC will also look to move forward with the same standard. HTC is one of the earliest adopters of OpenXR portability and had already built out developer resources well before their counterparts, however, as of this writing, it appears Oculus has followed suit and surpassed them in terms of support on the development side.
A number of leading organizations and companies have also come together to create the Metaverse Standards Forum, which is being created to foster interoperability standardization for an open metaverse. Simply put, this will be a consortium to collaborate on a standardized framework, the likes of which OpenXR has already developed and deployed at least for the XR industry.
What is OpenXR?
OpenXR is an open, royalty-free standard for access to virtual reality and augmented reality platforms and devices. It was first introduced by the Khronos Group back in 2017 at the annual Game Developers Conference (GDC). It was later released as a professional version for developers in March of 2019, and that’s when we first got our hands on it. OpenXR was created to form a baseline for development across virtual and augmented reality devices.
What does OpenXR mean for the future?
As mentioned earlier, OpenXR will evolve as a standard in place for the development of virtual and augmented reality applications. We will begin to see applications using similar frameworks for development which will create apps that are device agnostic and can be run on any device. Similar to how we have games for both Xbox, Playstation, and PC – We will begin to see uniform applications for all major hardware platforms and device types (Pico Neo 3, Quest 2, HTC Vive Focus 3).
This will also apply to PC-powered VR devices as well as AR headsets in the same way as the current standalone ones. This means current AR devices like the Microsoft Hololens 2, and even legacy VR devices like the tethered Oculus Rift S. The OpenXR cross-platform standard will get full support from others in developer preview form, with extra backing from the key chipset and XR accessory makers.
This might not seem that impressive to the layman, but the reality is that supporting all these devices meant that both Oculus and Microsoft had to release OpenXR compatible runtimes for both Intel and ARM architectures. This means that for both developers and businesses alike, the same applications will be able to run across PC-powered headsets, standalone Android-based headsets, and even HoloLens mixed reality goggles – all of which will save a ton of time and money in the development of universal virtual experiences.
Developer previews are also underway for two other high-end devices on the market; The Valve Index – a SteamVR-based headset and Varjo, an immersive mixed reality headset that focuses on ultra-high-resolution simulations. With all of this adoption and industry support ramping up from all sides, we can expect to see more and more adoption as momentum builds for the OpenXR standard.
The Role of Big Data Analytics in Accounting
Companies generate enormous amounts of data that need to be processed to produce readable insights and outcomes.
Big data analytics in accounting is a game-changer as it’s improving risk identification and real-time access to data and reporting.
More firms are increasingly adopting newer technologies to make them more efficient. This includes blockchain, artificial intelligence, machine learning, robotic process automation, data analytics, etc. The use of traditional accounting has disrupted the world of accounting, but with the onset of big data analytics, it has gone leaps and bounds, tapping into the untapped potential of any business.
Use Cases of Big Data Analytics in Accounting
Businesses accumulate tremendous amounts of data that could go into petabytes and zettabytes. The accounting function in any organization records all types of financial and non-financial transactions, collects them and analyzes them using predictive models to find actionable insights. Data analytics is all about making sense of the data received and thus, it takes away the hassle of traditional accounting. Let’s dive into why you would need to transition your business from using conventional to big data analytics.
1. Real-time Reporting
One of the biggest USPs of using big data analytics in accounting is its real-time reporting functionality. Most of the analytical tools available today are cloud-based, making real-time insights and reporting more accessible than ever. As big data deals with a trove of data, it crunches historical data in terabytes and even petabytes to find actionable insights.
2. Real-time Access
Another characteristic of using data analytics in accounting is real-time access. As it is cloud-based, it has the upper hand in timers of data visibility across different functions in an organization. It can be accessed concurrently, and different users can have different privileges for access.
Apart from that, the data syncs so that the changes made in one node are easily accessible on other nodes. This improved access to information in real-time with transparency makes decision-making easier.
3. Risk Identification and Mitigation
Certain risk factors can prevent a business from outperforming the revenue it hit last quarter or against the rival. Big data can help find risks associated with financial services, such as the supply chain, fraudulent transactions or activities, liquidity, data breach, etc. Businesses can use all the data and add it to various algorithms to anticipate or predict possible outcomes or track fraudulent activities in the books. As accountants can now find errors and risks sooner, the chances of propagating from the point of no return diminish.
4. Data Visualization
Making sense of voluminous data is impossible without using tools such as Tableau. It is a heavily used data visualization tool for big data as it helps find the flow, pattern and irregularities in the dataset. Analyzing the visualized data can assist in making business decisions and strategies needed to adhere to in the future.
Big data analytics in accounting can be a significant driving force toward many use cases. It includes predicting sales performance on food, travel, hospitality and others across different data sources, such as Booking.com, Yelp, etc. It can reduce downtime and operational costs thanks to monitoring IoT sensor data.
Companies can use data analytics in accounting to zero fraudulent activities. Optimizing labor and staff requirements is another chunk of issue that can be curbed using big data based on prediction analysis.
Organizations worldwide are leveraging the power of big data analytics in accounting over the traditional approach. It is because of the many benefits that it brings to the table, including real-time data access and reporting, data visualization, data audits, and others.
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