Improve Forecasting by Simplifying Data Analysis with ZEMA
Forecasting is an essential part of running a business, and historical data is a vital component of forecasting. Done correctly, forecasting helps a company plan ahead and increase its chances of remaining profitable. When it comes to data, the challenge for many companies today is finding a way to analyze abundant amounts of data in a way that provides useful insights.
The majority of companies rely on spreadsheet software, particularly Microsoft Excel, for their data analysis. As analytical needs become more complex, advanced data management and analysis software become increasingly necessary; the right software can simplify the analytical process, and significantly reduce the time it takes to organize data and build models in Excel. Eliminating time-consuming manual processes means more time can be spent deriving conclusions and decisions from the analysis.
As a simple example, as part of developing future price projections, it is required to determine whether there is a seasonal pattern in the historical price movements. In order to do so, the data would first need to be organized in Excel. The greater the volume and variance of the data involved, the more time consuming this organization process will be. Further, the data will need to be aligned; for example, if hourly data is being used with monthly data, the values of the monthly data will need to be repeated alongside the hourly data. If a company would utilize this model on a daily basis, the ranges would have to be updated every time the worksheet is updated with new data- adding more time into the process.
Accounting for weekends, holidays, and business days requires manually entering those tables and setting up the conditions into the worksheet. Every time the worksheet is updated with new data, the table will need to be updated as well. And this is only a fraction of the total process of developing price forecasts.
Streamlining Data Analysis with ZEMA
With ZEMA Market Analyzer, the entire process is simplified.
Performing a calculation such as the above example is as easy as dragging-and-dropping the relevant data series into the analytics pane in Market Analyzer; dragging-and-dropping the required formula into the formulas pane to apply to the data series; setting the date range; and then submitting the query. This process can then be automated so that all the user ever needs to do is look at the results.
The graph below shows a monthly forward curve built in ZEMA. Building this graph takes no longer than ten minutes in ZEMA; a process which could take upwards of half an hour using spreadsheet software.
ZEMA makes data analysis faster, smarter, and easier:
- ZEMA has dynamic logic which doesn’t need to be manually changed.
- Data is updated automatically via Data Manager.
- ZEMA has customized security settings, and the ability to revert changes at the push of a button.
- ZEMA has the ability to automate computations and push the results to downstream systems.
- ZEMA is designed to work with time series data. We have more date formulas and date based analysis tools than Excel such as DAY_OF_WEEK, built in holiday schedules, and more.
To learn how the ZEMA Suite can meet your data management and analysis needs, book a free demo now.https://blog.ze.com/our-industry-views/improve-forecasting-by-simplifying-data-analysis-with-zema/https://blog.ze.com/wp-content/uploads/2013/05/iStock_000021990386XSmall.jpghttps://blog.ze.com/wp-content/uploads/2013/05/iStock_000021990386XSmall-300x289.jpgIndustry ViewsThe ZEMA Solutionanalysis,business,data,data management,data management system,Data Manager,enterprise data,Enterprise Data Management,market data,ZE,ZE PowerGroup,ZEMA,ZEMA 4,ZEMA SuiteForecasting is an essential part of running a business, and historical data is a vital component of forecasting. Done correctly, forecasting helps a company plan ahead and increase its chances of remaining profitable. When it comes to data, the challenge for many companies today is finding a way to...Joanna MusialaJoanna Musialajoanna.email@example.comContributorBlogs by data management Experts & Analysts | ZE