Our Head-End System Enables Enterprise Information Management

Sieco-Tech utilizes a scalable, secure, and resilient cloud-based data management platform that acts as the foundation of our smart meter architecture. This enterprise platform collects, visualizes, manages, secures, reports, and delivers important metering data to authorized parties.

We are in the Information Age, and the demand for knowledge and insight in context and on time is rapidly increasing. We empower our clients with data analytics capabilities that allow them to enable their consumers lower electricity usage in practical and convenient ways.

Let our world-class smart meters do the measuring, and our advanced software platform do the collecting, storing, and processing of data for a winning combination that benefits everyone.

 

Our ERP system Connects the Complete Value Chain for Sieco-Tech

From customer ordering to production in the factory to sealing at the sealing shop to installation in the field – all are driven by one system. These automation processes minimize errors and redundancies and maximize operational efficiencies.

Data Management

Managing data correctly is not simple, because data by its nature has properties that present opportunities and challenges unlike any other asset. First, and more importantly, data is not consumed by its use and can be shared to an almost infinite degree. However, because it is so easily shared and is most valuable when most available, data ownership and security is a very important challenge. Second, in today’s age of connected smart devices, data grows organically both in breadth and depth, and having the technology and skill to properly manage this growth is crucial. Finally, data is often much more complex then it appears on the surface –the associated metadata must be brought along with the data to truly understand the context and what the data means.

Because of these inherent difficulties, despite many organizations’ best intentions, their approach to data is half-hearted and chaotic, and their execution is undisciplined. In contrast, our data platform applies a consistent and proven methodology that ensures the effective management of accurate, trusted data. Core elements of our data platform methodology include managing the data lifecycle, data classification, data quality, data governance and security, and reporting and data visualization.

 

Our platform manages the data lifecycle by progressing through seven distinct but interconnected steps:

  • Step 1 – Data Origination & Capture: Measuring the readings.
  • Step 2 – Data Validation: Validating the integrity and structural quality of the data.
  • Step 3 – Data Processing: Classifying, sorting, searching, and calculating to transform data into meaningful information
  • Step 4 – Data Integration: Transferring the data into all required standardized formats.
  • Step 5 – Data Aggregation: Consolidating data to perform validity checks, clean erroneous data, reduce duplicates, and present in a unified form
  • Step 6 – Data Interpretation: Analyzing, synthesizing, and evaluating data.
  • Step 7 – Data Stewardship: Managing, owning and protecting data in an ongoing fashion.

Classifying incoming data is an absolutely critical step in understanding what is being delivered, deciding where it needs to go, determining the required level of data quality, and effectively retrieving and utilizing this data going forward.

Our cloud-based big data platform applies intelligence to most accurately classify all incoming data to its most applicable and appropriate classification.

This process can include investigating and following classification aspects to make accurate determinations:

Data Quality is an immensely important facet of any data management platform. Processes and systems focus on data quality work to ensure an organization’s data is reliable, consistent, up to date, free of costly faults, and of sufficient quality for its purposes.

One insightful adage states that bad or “dirty” data is like a virus: there is no way of telling where and how many times it will turn up or the harm it will cause. Consequences of poor data quality include financial impact, marketplace impact (poor trust, confidence), productivity impact (increased workload, decreased throughput and efficiency), and risk and compliance impact. Mistakes in data can cause expensive billing, compliance, and liability issues that are costly and time-consuming to correct.

The accuracy and integrity of the data can only be relied on if it is of sufficient quality. Sieco-Tech understands this, and ensures that our clients will always have utmost confidence in the data produced and stored in our meters and systems. Data completeness and accuracy are a top priority for us, and drives our advancements in technology deployment, process management and data control systems.

Data governance is focused on understanding and controlling how all data enters the system, who is accountable for it, how to maintain clear transparency over the data lifecycle, data resilience, data redundancy and availability, and always maintaining and ensuring high standards of data quality and data security across the system.

Sieco-Tech’s secure data management platform is built with data governance and data security from its core foundations. This includes secure metering devices, enterprise level cloud security, data redundancy and archiving, high availability, effective authentication and access control mechanisms, integrated defense in depth across the devices, communications, and Head-End System layers, always-on auditing and alert notification system, and strict firewalling of customers data from each other.

Data governance and security matters. Our data platform is on the job 365 days a year.

Useful data reporting and maximizing our customers’ ability to do meaningful data analysis are important end-products of our data management system. Having a single, accurate, complete version of the truth provides our customers with the raw material for countless reports that provide valuable insight. The possible permutations and adaptions of these reports to dynamically changing business needs are virtually limitless. Our customers receive the information that they are most interested in, when and how they need it.

Our data platform allows the analysis of data to occur at every scope that is relevant to our customers: at the meter point level, the suite level, the meter panel level, at the entire building level, and even larger scales.