Monitoring the Dynamics of Global Energy Production with Alphacast

New Global Energy Databases in Alphacast

By Martina Mas(

Read more Alphacast Highlights here

We are happy to introduce two new data sources to explore global energy trends.

The first one is the Energy Institute which plays a privoral role in collecting, analyzing, and synthesizing extensive data related to the energy sector. With a focus on global insights, Energy Institute's datasets covers 154 countries. These resources grant access to crucial data on energy consumption and generation, carbon emissions, energy prices, and various other energy-related metrics. Secondly, the U.S. Energy Information Administration (EIA), the independent agency of the U.S. Department of Energy.

Multicountry Data Integration

In this segment, we are introducing our dataset of Electricity Generation which collects yearly data in Tera-watts per hour (TWh) for electricity generation from coal, natural gas, oil, fuel, and other significant sources. Given the wealth of available information, the following analysis of global energy generation involves utilizing the Filter Entity option to identify the five leading countries based on their respective contributions to the production of each energy type.

As perceived, in Alphacast, you gain flexibility to create a diverse range of charts, including line charts, scatter plots, and stacked charts. Among these options, stacked bar charts are particularly valuable as they provide an effective means to visualize and understand the relative importance of each country in the total.

Let's explore more examples of these bar charts, this time using our datasets related to Renewable Energy, Hydroelectricity, and Nuclear Energy.

In light of the information handed over, it is apparent that China, United States, Russia and India have emerged as the dominant players in all sources of electricity generation.

Nation-Level Data

With Alphacast, it becomes possible to aggregate similar information into a single chart efficiently! Just through pipelines, our feature Merge with Dataset enables you to combine multiple datasets. For more information on how to perform this step, we recommend referring to this guide.

This powerful tool provides an effective way to present a vast amount of information and allows you as an user to create a holistic view of interconnected data points. As an illustration, we have amalgamated data from four distinct datasets for the United States, Brazil, and China using Alphacast's powerful features of data consolidation.

Furthermore, Alphacast provides the ability to transform the data, facilitating the illustration of relative changes and comparisons across different time periods. In this case, the relative change feature allows us to visualize fluctuations in each energy type over the past 10 years. Anywise, there are other available options when you go to customize the chart, such as the running sum toggle, stocked toggle, and year comparison toggle. To explore these features, simply navigate through our platform and interact with each of them.

Mapping Energy Data

Alphacast offers a diverse range of data visualization options beyond traditional charts, with interactive maps being a prominent feature. Particularly for global datasets, such as energy-related information encompassing numerous countries, maps serve as an invaluable tool.

In recent years, the utilization and generation of renewable energies have become a consistent and impactful trend. Here our dataset Activity & Production - Global - Energy Institute - Renewables encompasses yearly data on a diverse array of renewable energy sources. Among these renewable sources, solar energy has emerged as the most prominent and significant one because of its abundance and sustainability.

Alphacast provides a diverse range of functionalities beyond maps, it harnesses the full potential of artificial intelligence. The integration of AI into pipelines empowers data professionals to effortlessly and rapidly create amazing transformations just by selecting our step ChatGPT Transform. As it´s demonstrated in the example above, we efficiently computed the average solar energy generation per country over the past 5 years. The result is that China, the United States, Japan, India, and Australia are the nations that showcased the highest average solar energy generation 2018-2022, each surpassing an impressive 60 TWh per hour.

Analyzing Data Across Continents

Plenty of our datasets also provide the information you may need for groups of countries or continents. Using the dataset Activity & Production - Global - EIA - Electricity we can analyze the world's energy production versus the most crucial countries inside the energy sector.

By leveraging Alphacast's powerful filtering tools, you will gain the ability to visualize information across all continents, making insightful comparisons with the global total. Beyond just energy values, the use of Pipelines enables you to employ predefined transformations, elevating analytical capabilities to new heights. In order to inspect all possible transformations you may utilize it for analyzing, simply check here.

To explore our extensive Global datasets comprising energy information, click here

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