Published By Guest Author, Alexia Collier
Modern technology, through the use of data, has streamlined processes in all sectors. In particular, the oil and gas industries now use data-recording sensors in everything from exploration to drilling and extraction. Over time, these industries have become very data-intensive and need sophisticated tools to navigate an ever-increasing amount of information.
However, it's not enough to just have these tools. Oil and gas corporations must also have the skills needed to use them. With a 2020 report from Petroleum stating that 90% of the data generated in these industries remain unstructured, this need is more pressing than ever. Fortunately, if your organization is looking to analyze your data more effectively, there are simpler ways for you to do so. Below are some of them.
Organizations require major physical infrastructure to both accommodate and analyze large amounts of data. However, having in-house servers can be costly. For this, the cloud can affordably meet all your storage needs. It's easily scalable, too, so you only pay for how much space you use. Your data will also be accessible anywhere to be analyzed, including outside the office.
More importantly, you won't have to worry about losing your data to power outages or other events. That's because the servers in cloud data centers have PCBs with high power integrity, which increases resistance to sudden electrical shocks or losses. What's more, you don't need to pay for the upkeep of cloud data centers, making them more cost-effective than in-house servers.
Data warehousing is a tried-and-tested method for data analytics. It's reliant on the "extract, transform, load" (ETL) process, which copies data from one or more sources, transforms them, and places them into a new destination system. Arguably, it's the foundation of data analytics and machine learning.
However, ETL requires a lot of manual work to be properly developed and maintained. Writing scripts alone can be prone to error, and the troubleshooting that may be required afterward can be time-consuming. Thankfully, platforms like Panoply and Qlik Compose now provide cloud-compatible automated ETLs with simple visual point-and-click interfaces. These allow data integration specialists to streamline ETL integration workflows with just a few clicks.
If you need a quick and easy solution to your data analytic woes but don't have skilled software developers on hand, low-code and no-code development platforms like Quixy and Zoho Creator are your best friends. Much like ETLs, these tools have highly visual interfaces. Both platforms even use an easy-to-use drag-and-drop format so users can combine components and even third-party APIs of their choice, without having to write code line by line. As such, even those with rudimentary software development skills (or those with none at all) can customize applications for specific purposes like data analytics and create effective ETLs.
This modern innovation can bring your organization's data analytics to the next level. It allows you access to all your data from a single point, whether it be from the cloud, traditional servers, or third-party providers. It can even perform faster and cheaper than ETL platforms, with capabilities to analyze data as it's generated. Notably, Datagration provides a universal view of your organization and manages security and access in real-time. This allows you to gain, act upon, and get the most value out of key insights faster than ever before. Ultimately, data virtualization promises your organization significant business value acceleration.
In the end, by more effectively analyzing your data, you can do more than make better high-level business decisions. The tools mentioned here can be used to optimize upstream practices, conduct preventive maintenance on your machinery, improve your safety protocols, and streamline offshore operations, as well. Indeed, your organization can flourish in today's age of Big Data.