What is Data as a Service?
Data as a service, or DaaS, refers to exchanging machine-readable data for something of value between two or more organisations, according to Wikipedia. However, this definition is not the only one and what constitutes 'DaaS' varies depending on interpretation.
Some interpretations do not restrict the data to being machine-readable only. Others omit the value exchange part to incorporate organisations that provide access to data for other reasons rather than profit. Many interpretations refer to cloud computing.
However, the general idea behind all these varying interpretations is that one party provides data to another.
Data as a Service
It is ground zero - raw data that still requires the acquisition and a great deal of effort to use (typically, cleansing, enrichment, transformation). It is not consumer-friendly. Sometimes it's big data that cannot be used without a specific set of technologies that can deal with its sheer volume or velocity—for example, satellite photos and vehicle traffic.
Information as a Service
One level above DaaS. The information provided could be used as is and may or may not require additional data acquisition or processing work.
One method of distributing this information is via websites. In this case, data resides solely on the DaaS provider side. A website offering business information about companies, like Crunchbase, could be considered an Information as a Service platform.
Analytics as a Service
The next level includes visuals such as maps, gauges and pie charts, and means of self-service data analysis, including aggregation, filtering and transformation among others. Data acquisition is not required.
Insight as a Service
The top level is about providing predictions, prescriptions, what-if analysis and other insights, more often than not powered by machine learning and deep domain knowledge.
It's worth mentioning that vendors often offer a package deal which combines the services mentioned above. For example, the European gas market analysis platform appygas provides a map of gas flows, planned route maintenance information (falling under Analytics as a Service), and a route calculator for what-if analysis (falling under Insight as a Service).
The problem with the above categorisation is that the two last concepts are often used to describe software-based offerings. To avoid complications, we will use DaaS as a generic term that covers all these concepts, yet keep in mind the variety of different service forms.
Unlocking the value behind the DaaS platform
Companies may turn to DaaS for several reasons, including if acquiring the data is their only option or if it is easier than creating it themselves.
The pitfalls of data collection & management on your own
Before moving to the advantages of a DaaS, let's look deeper into the problems with collecting or managing data on your own to see why the DaaS market appeared.
- Increased data cost. The cost of gathering, creating and processing data internally with development resources and infrastructure is more expensive than one might initially think. The price is not flat or transparent due to the many hidden or unexpected expenses involved. Let's say we need to extract a few datasets from a website—not the most developer-friendly data source. The data-acquiring process may be complex, including multiple interactions with the website that may be required to display the desired data. Maintaining a web scraping solution is even more challenging and expensive due to occasional changes on the scraped website. Moreover, after obtaining the information, you need to clean, transform and store it in a way suitable for analysis. Then you'll need to design business intelligence dashboards. Now imagine that instead of doing all this work yourself, you could simply receive ready-to-use dashboards and reports.
- Longer time to deliver insight. Not only does the example above cost more to do on your own, but it also takes considerably longer to implement.
- Data governance and quality. Maintaining data quality requires effort. Typically, the best solution to this is a data stewardship process. It relies on dedicated data stewards who spend significant time ensuring data assets are clean, up-to-date, available, documented, secured, and conform to the company's data standards.
- Ensuring compliance and enforcing security is pivotal. Storing sensitive data is an integral part of the data management strategy and should not be treated lightly, which of course, comes at a price.
- Documentation, ease of use and availability of business data are just some of the many things that need to be considered.
- And finally, as mentioned above, there are cases when collecting data on your own is not feasible due to the enormous investment needed. Weather data (forecasts or historical) or satellite images are prime examples. Buying them is easy, and while not cheap, there are multiple options to choose from, but making satellite images requires, well, a satellite.
Benefits of the DaaS platform
The advantages of DaaS below relate to the issues previously mentioned:
- Reduced costs, both direct (data acquisition, data storage, data integration, etc.) and indirect (maintaining data quality etc.)
- Reduced time needed for users to start getting the value out of data (sometimes it's close to zero and boils down to buying a license and logging into a web portal)
- Easier to enable data-driven decision-making and build a data culture if the information is accessible via a click or two
- Simplified compliance (no need to care about the physical location of the data assets, retention periods, and so on)
- Better and more transparent budgeting
DaaS platforms typically remove the pains of data management listed. Although they can still be prone to problems like data quality and availability, in most cases, you have a strict SLA defined by a service provider that will help protect you from these risks.
Energy Data as a Service (EDaaS) explained
The energy sector is one of the most data-intensive industries in the world. Every day, energy companies generate and collect vast amounts of data from power plants, transmission and distribution networks, and customers. This data can be used to improve operations, reduce costs, and provide better customer service.
Businesses are always looking for ways to manage their data more effectively, and energy software is a great way to do this-as with the help of Energy Data as a Service (EDaaS).
Enterprises can use EDaaS to track power usage trends, monitor equipment performance, optimise operations, and more. It is also easy to share this data and collaborate with partners and customers.
How the energy sector is changing
The energy sector is in the midst of a transformation. It has been shifting to renewables, low-carbon technologies and even net-zero solutions for years. Almost 200 nations have agreed to curb global warming by reducing greenhouse gas emissions and transitioning from fossil fuels. The energy transition is a worldwide movement from fossil fuels such as coal and oil to renewable sources like wind and solar.
What's more, Europe has traditionally relied on Russian natural gas supplies. But with Russia's recent invasion of Ukraine and subsequent pressure on the energy market, the European continent is now looking to reduce its reliance on Russia and move towards alternative energy sources.
LNG terminals and renewable energy sources are viable options for Europe in the future. However, the transition from Russian gas will be a process that takes time. Moreover, natural gas prices are six times higher than in 2021, putting strain on European leaders who have also made ambitious climate promises.
In these difficult times, making data-based decisions is more important than ever and may become a competitive advantage.
Data in the energy sector: what is on offer
The number of companies that provide energy data or energy-related data is immense. This list is in no way comprehensive and only represents a tiny fraction of the information made available by DaaS providers. There’s information about:
- Individual and corporate energy usage that helps understand consumption patterns and future forecasts
- Energy stock market (stock price, transactions)
- Energy prices (exchange and OTC) and vendors
- Current power production (location and output of hydropower dams, nuclear power plants, wind generators and solar farms)
- Volume and geography of exploration, production, transportation, storage and refining of fuel sources and crude oil and as well for natural gas (excluding refining)
- Electricity transmission and distribution network
- Shipping and storage of LNG and pipeline transportation of natural gas
- Energy companies (performance, headcount, etc.)
- Meteorological data such as wind (speed, rose and power density potential), solar irradiance and hydro reservoires that can be used for better planning of energy production
- How the world is progressing toward Sustainable Energy for All (SE4ALL) via The Global Tracking Framework (GTF)
Given that most companies now use data to inform their decisions, it's no surprise that Data as a Service is becoming increasingly popular. This approach to data management can help organisations reduce costs, simplify compliance and improve budgeting transparency.
Data is present in many industries, but data-intensive ones like energy can benefit the most from DaaS solutions. Many companies in the DaaS market, like appygas, provide Energy Data as a Service. In today's changing energy market, having timely insights can give companies a competitive advantage and help them weather any storms.
If you would like to explore more about how DaaS or EDaaS can benefit your business, get in touch with us today.
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