Power BI is great when it comes to data visualization and dashboarding. In complex utility landscapes, these are good to have but definitely not enough. Sure, you can view all the events or developments that occurred over a period. But do they turn those insights into action, at the pace that modern data ecosystems demand?
The answer is, sadly, no.
What enterprises, especially Utilities, need is a solution that takes into account the entire data lifecycle. This is where Grid excels, acting more just than a data visualization layer, but as a comprehensive operational data management stack, to handle your entire data pipeline.
Understanding PowerBI’s Data Storage Models
PowerBI does not have its own native data storage model, but comes with an in-memory engine called VertiPaq. Data gets stored in a columnar format, where VertpiPaq compresses the information and stores it in-memory for queries.
Let’s explore the different data storage models:
Data Import Mode
- Data is imported into PowerBI from external sources like Excel sheets, SharePoint, SQL databases, etc. Once imported, the data is compressed and stored in-memory by using VertiPaq.
- This model allows for faster queries but requires manual refreshes to ensure the data is up-to-date.
Direct Query Mode
- Data resides in the source system (Oracle, SAP, Azure SQL). When a user interacts with a visual, PowerBI sends live queries or requests to the source. Power BI does not store any of the information, but acts more like a window into your fresh data.
- The time taken for query execution will completely depend upon the performance of the source system, along with factors like network latency and concurrent load.
Composite Mode
- This model combines Import and DirectQuery in the same report. For instance, you can import sales data over the last 2 years and use DirectQuery to view present day transactions (latest data).
- The process might be slower since the system needs to embody results from two sources with varying latency profiles.
Although these models offer flexibility in data storage, Grid takes it a few steps further. It eliminates the reliance on external data sources and provides integrated data management capabilities for real-time operational analysis.
Grid is primarily designed to reduce dependencies on external data sources, with a platform that natively stores and contextualizes information. It goes beyond visualization, bringing a unified architecture for ingestion, processing and storage of utility data. The platform comes with utility specific connectors, and a native ODS (operational data store). What does this mean for utilities? — Both operational and event-driven data co-exist, with an intelligent layer that enables automation of tasks, field execution, SLA tracking, and more.
Comparing PowerBI vs Grid in Managing Data Pipelines
Beyond Dashboards: Grid’s Case For a Real-Time Operational Intelligence Layer
The journey to attaining utility intelligence does not begin at dashboards. It starts much earlier. When your data is not traceable and constantly updating in real-time, your enterprise risks walking along blind spots in mission-critical environments.
Grid addresses this loophole, with an added operational layer. One that aligns all your data, systems and assets into one coherent and interconnected model. It may be the time for your organization to truly rethink your data infrastructure, above and beyond dashboarding.
Explore a more outcome-driven approach to operational data management, and make utility decisions with greater precision. Connect with our experts today and find out how.
FAQs
Does Grid Replace Or Complement PowerBI?
Grid can complement PowerBI as per organizational requirements. It can also be adopted as a standalone solution, with its native-domain framework becoming an advantage in mission-critical environments (outage response, operations & maintenance, device monitoring).
Is Grid easier to deploy when compared to PowerBI?
PowerBI is built for business analysis, offering drag and drop interfaces and quick dashboarding. Grid is optimized for utility workflows, offering native-connectors for AMI, SCADA, HES, GIS, etc., reducing onboarding time and the need for manual set up or custom connectors.
How does Grid differ from PowerBI when setting up alerts?
With PowerBI, utilities can set up basic alerts, such as a KPI crossing a threshold, or predefined value. Grid takes it a step further, with real-time triggers based on operational rules, like breaches in SLA, device not communicating, transformer failures, abnormal consumption patterns, etc. Alerts on Grid are also automatically routed to relevant stakeholders or systems.
Is Grid scalable for large datasets and operations across multiple locations?
Yes, Grid is scalable to handle and work with high-frequency utility data from millions of endpoints. The platform also sustains high-performance and maintains operational accuracy across multiple regions.
