The Data Management Challenge – Making Sense of Data for Energy and Commodities
It’s no secret that data is big news right now.
As technology continues to advance, we find ourselves more and more inundated with new data. Take for example the natural gas markets where locational pricing alone can produce more than half a million data points daily. Or electricity, where we’ve been watching markets transition into nodal reporting.
In the absence of a rigorous collection methodology, taking the time to manage vast amounts of data isn’t easy.
And this is before we even get to the actual number crunching stage.
Every analyst, manager and trader requires timely access to clean market data. Securing this for your company can be a full time job. Or is it?
For those of us working in the world of energy and commodities, utilizing the right business intelligence data management system to make sense of millions of data points will create that competitive edge.
The four steps below will help your company reduce the amount of time spent finding data and instead give you more time to start making sense of it.
Step 1: Identifying Your Data Requirements
Sourcing the right data is one of the biggest challenges starting out. For example, if you’re tasked with developing forward curves you might be required to access information from broker quotes, exchange prices, historical spot prices and FX rates … maybe more. The invoicing process will require you to work with settled prices and consumption data as well. It’s important to ensure you are working with the right information from the get-go. Establishing your requirements will require diligence and effort.
Step 2: Determining Where to Get this Data From
Companies usually target a large volume of disparate data sources with unique formats such as PDFs, Excel Files, text files and URLs. Each of these sources can have their own unique extraction and formatting requirements. Some can be publicly available, others may need to be purchased from vendors (subscription data is very common). More data can be internally generated by a company itself. The key is to balance the cost of these data sources (including those that aren’t free) against their validity, their ease of capture, their usability and their ability to integrate with your other data sources.
Step 3: Collecting, Organizing and Storing this Data
It can take a lot of people, money and time to collect the right data for your company. Analysts often spend more time working on data collection than actually applying their analysis to it. Developing a company-wide self-populating database that ensures data is centralized and easy to access is … well …. crucial. Be warned this is no small task for any IT department.
Step 4: Implementing the Right Data Solution
How do you achieve all of the above without spending excessive amounts of resources and expense?
With the right data management solution. These solutions enables companies to quickly access data as well as enhance their planning, analytic and trading abilities. The good news is that there are powerful software products in the market that already provide these services.
At ZE PowerGroup Inc, we have developed an award winning data management suite – ZEMA – to meet the requirements of those working in energy and commodities. ZEMA’s powerful automated data capturing application – ZE Data Manager – will give you access to real time and historic data from any electronic data source. ZE Data Manager is fully integrated with our sophisticated web-based application that automates the extraction and analysis of the data – ZE Market Analyzer.
ZEMA makes sense of data and can provide your company with excellent ROI.
https://blog.ze.com/the-zema-solution/the-data-management-challenge-making-sense-of-data-for-energy-and-commodities/https://blog.ze.com/wp-content/uploads/2013/02/zema_blog_1.jpghttps://blog.ze.com/wp-content/uploads/2013/02/zema_blog_1.jpgThe ZEMA SolutionIt’s no secret that data is big news right now. As technology continues to advance, we find ourselves more and more inundated with new data. Take for example the natural gas markets where locational pricing alone can produce more than half a million data points daily. Or electricity, where we've been...Denise DonovanDenise Donovandenise.firstname.lastname@example.orgContributorBlogs by data management Experts & Analysts | ZE