The abundance of data changed the way we work and live. What was largely isolated to mathematicians and statisticians is now ubiquitous throughout every industry hoping to digitalize and transform their organization into a relevant player in this day and age. Big data comes with some big baggage. In fact, it comes with the whole package. Many of the questions we ponder have answers that lie in the data we have access to, but it’s up to us to figure out the combination. With so much potential in this data, and so much weight in knowing we are the only thing standing between us and the answer, our future with data is truly what we choose to make of it as we aim to fix each problem we come across with our utility data analytics.
Organizations build their analytics departments in search of data-driven answers. But it’s not just the data that’s crucial, it’s the people in these departments that play a crucial role in unlocking that potential. A data analyst, data scientist, or even your intern running all your data through R, are all invaluable to your team. Your organization hired these people for conducting analytics and answering your business questions through data. Unfortunately, much of their daily workload consists of low-value work that can easily be avoided so that these individuals can spend more time truly extracting value from the insights the data provides. Most of these individuals spend the majority of their time accessing and gathering data from multiple sources, synchronizing data, or data cleansing just to have datasets ready for performing analytics. Though a necessary evil, it is low-value work like this that inevitably hinders an organization’s most valuable minds from truly doing their best work. Fixing that issue would ultimately lead to astounding results for the organization and more value from both your data and team members.
Take a look below to see the key pain points faced when attempting to analyze and use data to make decisions, and how to go about solving them.
1. Scattered utility data in multiple source systems
The whole is greater than the sum of its parts, and having disparate data sources siloed throughout your organization leads to a lack of ability to collaborate and make well-informed analytical decisions. This is a known struggle of any data analyst and why Awesense centralizes all our customers’ system data in our data layer. This means GIS, CIS, Asset Data, SCADA, smart-meter, EVSE, SolarPV, Storage, IoT, and other sensor data is all accessible from the same location in a well-organized and described data schema. That is all possible because of our energy-focused data model design (data schema). It enables users with access to a highly secure and adaptable data system specific to the energy system that can view relationships and dependencies across datasets. The Awesense data schema has a rich attribute set that can accommodate a wide variety of information. These are the advantages which stand above many utilities’ data lake implementations. The Awesense data schema comes with the guarantee of a 3rd party vendor solution’s portability and a dramatic decrease in implementation costs for new solutions; this is because our data schema is the same for each utility.
What that means is that now users have all their data sources accessible from a single location. Data analysts can forget the tiring maintenance that comes from having an endless amount of data connectors linked to various data source systems, different connection technologies, data schemas/relations, as well as the headache of efficient data flow architecture. With Awesense, this problem is now one of the past.
2. Low quality of the utility data in source systems
No matter how good your analytics are, they don’t mean a thing if your data quality is poor. As the old adage goes, garbage in leads to garbage out. Data analysts in many utilities face the issue of low data quality which prevents them from delivering reliable analysis results. That’s why we created our unique validation, estimation, and error correction engine (VEE). This crucial process takes in and improves the data quality and corrects errors in the data, allowing for more value to result from any analytics run on that data thereafter. Our refined algorithms focused specifically on energy systems are tailor-made to solve errors that appear in energy data. Our engine’s capabilities go far and beyond generic VEE engines. In short, data in the Awesense platform rests at better quality than the same data in its original systems. As a bonus, data quality issues are reported back to original systems so that errors can be corrected at the source.
3. Synchronization of data & alignment in time and space
Time series data is a game-changer when it comes to in-depth analysis. The only problem is that not all time-series data synchronizes well with other time-series data. Issues like varying granularity of timestamps or time shifts are common pain points of data analyses. You can’t have time without space, which is why we believe that complete pictures can only be obtained if time-series data are aligned to their geospatial location of origin. We have all of that covered. Our platform automates the synchronization of different time series data sources as they are ingested into the system. Because all time-series data generated from devices in the energy system are connected with their geospatial reference, this gives data analysts the ability to see every device and asset’s behavior on a geographical basis. In addition to that, all ingested data is also synchronized with publicly available sources like weather, various map tiles, street views, and much more. We know it is all about having and seeing various data in different contexts, so we make sure data users don’t miss out on a thing.
4. Data Browsing & Data Exploration
When data analysts are conducting analytics, the first step is usually to conduct a visual analysis of the data. Data browsing and exploration can be a hassle when you don’t have a robust system in place. It is also difficult to have a unified interface for visualizing time-series and geospatial data from a variety of sources. Instead of trying to find the proverbial needle in the haystack, platforms like Awesense allow you to easily visualize and explore all your system data in a single user interface. Awesense’s True Grid Intelligence frontend platform offers powerful GIS and time-series browsing & exploration capabilities, solving this pain point and making it a gain point.
5. Simplification of Data Requests
Data should make the lives of data analysts easier, not more frustrating. This pain point may seem like an easy fix, but the reality is that simplifying data requests are often more complicated than they are worth. We changed that for many utilities and their energy data. Our platform allows for the aggregation & simplification of functions that provide data in a more digestible way without compromising any valuable information. This means more data, fewer requests, less complexity, and higher quality, all with the click of a button.
For example, our functions and API calls include the ability to call a meter for its max point of consumption over a specific time period. Moreover, it can even be used to request the number of transformers that are located downstream from a specific location in the grid (topological tracing). These are just a few simple programmatical functions offered by the platform. By using these time-saving techniques, data analysts can get more value from your complex data issues and lower the barriers to performing better, and more in-depth analytics for your organization.
6. Development Skills and Expertise
Nowadays in utilities, we see that data analysts take the form of anyone attempting to answer business questions through data. However, not everyone is fortunate enough to have the technical knowledge required to bring these ideas to life. Awesense believes in the democratization of energy, data, and analytics. Because of this stance, we offer analytical development techniques that range from very simple, such as low or even no-code applications, all the way to techniques for more advanced individuals looking to build robust applications needed to answer their simple and complex questions.
Worried about all the time and effort you’ve put into working with external tools like Power BI and Jupyter Notebook? Don’t worry, we make our customers’ lives easier by seamlessly connecting their data systems to external tools and applications such as Business Intelligence tools, data science notebooks, and planning tools to perform analytics, design algorithms, and operate the energy system. In fact, the more you connect to the Awesense Digital Energy Platform, the more you can do.
7. Documentation & Quick Start
Imagine getting a new piece of equipment without an instruction manual. That’s exactly how many users feel when handling a lot of data and experimenting with different tools. Awesense provides rigorous documentation tailored for data analytics for analytics development and quick start manuals that make that process a whole lot easier. In addition to that, the Awesense Marketplace includes a (still-growing) set of analytics applications which can be easily downloaded, forked, and modified based on your personal needs! This way data analysts can jumpstart their analytics or just browse through a library of what has already been done as a means of sparking up new ideas for their next analytics project!
A New Day For Data Analytics
Along with bringing value and streamlining certain operations, the dawn of data brought with it many problems for utilities and their data folk. Today we can finally say that this is no longer the case. The Awesense Digital Energy Platform and Open Energy Data Model allow utilities and energy providers to focus on what really matters and dramatically shorten time to value while performing data analytics. With the Awesense Platform, data analysts can easily build data-driven applications and analytics through our innovative product features. And these seven common problems faced by really anyone who works with utility data are just the tip of the iceberg when it comes to the limitless possibilities data provides.
Individuals working with data have spent too long on these issues, and even longer on menial tasks that aren’t serving them or their utility the way they should. By aiming to use the expertise of these now highly coveted individuals in your organization, in combination with a powerful platform like Awesense to enable their potential, the data game will never be the same. No longer will data be a hassle or a burden. No more wasted data or man-hours, and no more headaches for your utility or your customers. With the expertise of data employees and access to the right platform, all that’s left to do is for you to pick what order you want all those questions you’ve been asking, answered.
Need to see more?
Curious how our platform might benefit your organization and its data? Talk to one of our data experts and get a complimentary, customized demo, here. Have questions as to how we may be able to help and manage your data? Feel free to reach out to us at email@example.com, we’re always happy to connect!