Power BI Reporting: Edging The Way to Data Decentralization

Power BI Reporting

You’ve probably heard of the ongoing shift towards edge computing as being a paradigm complementary to cloud computing. In the past couple of years, edge computing has emerged as one of the ongoing IoT trends. In fact, MarketsandMarkets research shows the global edge computing market will hit the $9.0 billion mark by 2024 as more companies deploy the technology to improve operations. 

That said, there is a need for decentralization, given the increase in devices that process large volumes of data. Power BI reporting can provide a multi-perspective view of data, with visualizations that represent different findings and insights from the data model. 

Defining Edge Computing 

Edge computing refers to a distributed computing framework that processes sensor data away from centralized nodes and closer to individual data sources like local edge servers and IoT devices. It makes mobile computing for locally produced data possible – edge computing decentralizes processing power, thereby ensuring real-time data processing without the need to reduce bandwidth or storage needs of the network. 

It offers a broad range of unique value propositions (UVP) for IoT applications and different use cases across various industries. Some of the areas that will rely on edge computing to enhance security, optimize performance and increase productivity include: 

  • Autonomous vehicles: Autonomous vehicles are increasingly becoming common. But for these cars to replace human drivers, they must be capable of reacting to road incidents in real-time. It takes about 100 milliseconds for data to be transmitted between a vehicle’s sensors and the backend cloud data centers. Artificial Intelligence will give autonomous vehicles real-time decision-making capabilities, thereby enabling them to respond faster than humans would in case of a sudden change in traffic flow. 
  • Fleet management: Fleet management is another area where edge computing will come in handy. Logistics firms typically leverage IoT telematics data to ensure effective management of their fleet operations. Areas with poor signal strength and low connectivity often have limitations when it comes to volume and speed of data transmission between backend cloud networks and the vehicles. By using computation capabilities in close proximity to fleet vehicles, logistics companies will look for efficient network transmission strategies to make the most of fleet telematics data for the vehicles that travel to distant places. 
  • Predictive maintenance: Edge computing enables IoT sensors to keep track of machine health and identify any signs of time-sensitive issues that machines may have in real-time. Consequently, manufacturing companies can enhance operational efficiency and lower maintenance cost. Data analysis is conducted on the manufacturing premises, and the results are uploaded to the cloud either for reporting or further analysis. 

In a nutshell, supply chain management and location-based industries will rely on this type of information and communication technology upgrade to operate efficiently and cost-effectively. 

Benefits of Decentralization 

Decentralization of data addresses crucial infrastructure challenges, including bandwidth limitations, excess latency, and network congestion. But there are numerous other potential benefits of data decentralization that can make this approach ideal for other scenarios. They include: 

  • Data Sovereignty: Moving large volumes of data isn’t just a technical issue. The data’s journey across regional and national boundaries can bring forth additional problems for data privacy, security, and other legal problems. Decentralization of data ensures that it remains close to its source and within the boundaries of the prevailing data sovereignty laws, such as GDPR. This makes it possible to process raw data locally, thereby securing any sensitive data before any of it is sent to the primary data center or the cloud. This could even be in other jurisdictions. 
  • Autonomy: Decentralization comes in handy in areas where there’s restricted bandwidth or unreliable connectivity due to the site’s environmental characteristics. Decentralizing data means that you can work on it on-site. When data is processed locally, the quantity of data to be sent is vastly reduced, thereby requiring far less bandwidth or connectivity time. 
  • Edge Security: Decentralization through edge computing gives you the opportunity to implement and ensure data security. Whereas cloud service providers have IoT services and can conduct extensive analysis, enterprises still have concerns about the security and safety of their data once it leaves the cloud and is in transit. With edge computing, any data traveling back to the cloud or data center can be secured through encryption. What’s more, edge computing itself can be fortified against cybercriminals and other malicious activities. 

When Is a Decentralized Data Network Better? 

As in all developing technologies, there are times and places where the older version, such as cloud networking, allows platforms and other software-driven solutions to function with greater agility. The scalability of an eCommerce platform where users can congregate at certain times of the day may be the priority. 

In contrast, having server access closer to the end-users point removes the competition for bandwidth traveling to and from servers. In the case of data centers, there may be a long jam of compelling data packets that may cause longer latency periods. Edge computing enhances the responsiveness of systems because data gets to and from the servers much more quickly. Having more configurations where edge servers are closer to the end-users can dramatically improve agility and performance. A split second can provide greater safety, such as in the capability of an autonomous vehicle to identify and stop when a pedestrian is in danger. 

Decentralized data networks are enabling data generators to barter or sell their data without compromising their privacy, losing ownership control, or relying on third-party middlemen. Because of this, a decentralized data network has the capacity to bring the entire long tail of data generators into the emerging data economy. 

Faster Data Delivery Opens Some Interesting Possibilities 

Real-time data delivery can potentially skyrocket the competitive advantage of businesses in today’s marketplace. Retrieving that data for end-user intelligence can improve your business. 

With Power BI Report Scheduler, you can use the data in your database automatically & asynchronously to populate report body text, filters, email addresses, formats, and much more, and then generate, export, and deliver separate power BI reports to individual recipients. With it, you’ll simply define a package(s) of power BI reports or SSRS, run them automatically, and then automate the sharing of these reports.