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Big Data and Analytics For Solar

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Big Data Analytics for Solar

As the interest in renewable energy grows globally, solar energy has increased in popularity with both consumers and businesses. The Solar Energies Industry Association reported that in 2012, the U.S. markets installed a record-breaking 3,313 megawatts of photovoltaic capacity.  And large, well-known companies such as Apple are making the news for their  increased interest in using alternative energy to power facilities. As of March 2013, the mega-sized tech firm is depending 100 percent on renewable energy sources to power its data centers, according to a Bloomberg news story.  A neighboring 100 acre solar farm powers Apple’s largest data center in Maiden, N.C., and they have plans for another nearby solar farm to open later in 2013.

So what does this growing and large-scale adoption of solar power by big business mean for solar energy providers? Major opportunity to grow and expand. However, it also means  increased responsibility to organize, store, and manage vast amounts of data.

Big Data Analytics for Solar

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Turn Your Data Storage Requirements into Business Opportunities

Solar energy enterprises (like other renewable energy companies such as wind power businesses) may need centralized organization, easy data retrieval, and protection of sensitive data as part of federal or state regulated records management. Since you’re  required to keep all this data anyways, why not use it to make better business decisions, help customers, and find potential business opportunities? After all, there’s a ton of useful information hiding in all that data. Here are five ways big data and analytics can help solar energy providers.

Help Your Customers Get Their Solar Power Rebates

Solar energy has improved by leaps and bounds over the past few years, leading to interest from a growing number of homeowners. In some parts of the United States, homeowners and business owners are encouraged to install solar panels to generate electricity for their own use, as well as to sell it back to the local power authorities to power “the grid.” The process, known as “net metering,” requires careful monitoring of energy consumption to track who generates energy, as well as how much.

Homeowners and business owners who take advantage of installing solar power and net metering may qualify for  tax rebates or grants, as well as reduced energy costs.  However, to claim their incentives, they usually have to show documentation showing what they’ve installed, and how it’s improved their energy efficiency or reduced their costs.

Cloud-Based Records Management Speeds Up Data Recovery for Solar Clients

Solar energy businesses providing the equipment and services to customers must keep careful records of each transaction. You should be ready to give the information to your customers when requested. Finding that information quickly and easily with a cloud-based records management system saves the time, money and hassle of searching through paper-based records.

Save Time and Money Preparing for Energy Audits…or Litigation

While no one enjoys the prospect of a regulatory or government audit or being part of a legal inquiry or litigation, a solid records management system really cuts down the time, work, and cost of locating and retrieving the necessary documents, images and data required in such action – no matter what industry you’re in!

Comply With Alternative Energy Federal and State Regulations

Record-keeping to meet legal and regulatory requirements is a fact of life in most industries today. Depending on the location of a solar power enterprise, you may be required to meet state Renewable Energy Standards also known as Renewable Portfolio Standards — which are likely to change over time. A cloud-based records management system for your solar big data will help make sure your business is meeting the current requirements, and can also save a lot of time over paper-based records when the standards change.

As of March 2013, 29 states, Washington D.C. and two American territories have Renewable Portfolio Standards in place. (As of January 2012, the Solar Energy Industries Association merged with Solar Alliance, a group operating at the state level.)

Legacy Records for Solar Energy Performance Evaluation

Solar powered energy has come a long way in the past 20 years.  But just how far is “a long way?” To quantify improvements in energy efficiency, data going back many years is collected and analyzed – basically, a solar energy analytics program is applied to the big data over a set time period to find trends.

Convert  records of activities such as panel performance improvements, customer utility cost reduction, and increased efficiency into new formats to compare data from different time periods seamlessly. Again, the technology of big data and analytics for solar saves time and money for providers.

Analytics Uncovers Global Solar Opportunities

Are you running a global solar provider? If so, centralized data storage allows comparisons across regions, countries and continents to evaluate opportunities and performance worldwide.

Find New Markets and Product Lines

Well-organized data is more than simply large quantities of information; it may very well hold the keys to identifying new product lines, areas for improvement, potential new sales campaigns, new target markets, and future trouble areas in your own solar business as well as in the solar energy sector as a whole.  And thinking of data in these terms may point to profitable opportunities in the solar industry.  However to find the opportunities, your data must be organized in a sensible and methodical records management system, so data retrieval is easy, efficiently delivering the information needed to  feed new and developing analytics programs.

Final Word

Members of the solar industry are becoming aware of the importance and opportunity of data extraction, and they continue to voice concerns over several issues directly related to records management in the solar energy sector. For example, at the Solar Power International 2012 general session, Solar Electric Power Association (SEPA) president and CEO Julia Hamm mentioned performance monitoring, metering equipment and forecasting software as important technological issues that will affect the advancement and adoption of solar power in the future.  But in the meantime, take a look at your records management program. If it isn’t optimized to easily apply an analytics program that will help you help your customers, meet regulatory requirements, and uncover new sales opportunities, it’s time to look at a new system to organize your solar big data.

Behavioral Analysis of Big Data for Authentication: a Win/Win for B2B?

Big Data for Authentication
Big Data for Authentication

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Are you looking to improve your information security? If so, you’ve likely read up on adding authentication measures to your IT infrastructure, but do you know how to choose the best measures for your organization?  Here’s some good news. Applying analytics to big data for authentication measures has the potential to increase both security and user convenience – a win/win for both you and your clients.

Behavioral Analysis Boosts Risk-Based Authentication Measures

Protecting sensitive data while ensuring the right people have access to the right information and resources in an environment with rapidly changing technology is definitely challenging. The solution for many businesses across the globe and throughout all industries is to use a variety of authentication measures. However, authenticating users based on generic criteria isn’t nearly as effective as authentication measures incorporating specific behavioral analysis with a broad and diverse set of factors.

Big data analytics produces precise information about this behavior which can then be used to choose authentication measures best suited for a mid-size business, enterprise, or organization.

Mining Big Data for Usage Patterns: How it Works

Interactions with systems and applications create device usage patterns and behavioral characteristics over time.  And the more people use systems and applications, the better the data will be when eager behavioral analysts (or the behavioral analytics software) start combing through it.

All of this data contributes to the creation of robust user profiles – profiles which are key to risk-based authentication measures.

Risk-based authentication implements measures that verify user identities for each and every session. The current user behavior is compared to their past behavior in previous sessions – the information that contributes to their user profile.  If the current behavior is consistent, access is granted. If it isn’t consistent, the user may be denied access or asked to authenticate with additional factors for verification before access is granted.

Search Big Data for Authentication Clues and Save Money

Risk-based authentication is a cost-effective way to expand controlled access to an organization’s virtual private network (VPN). This is particularly useful when working with temporary employees, contractors, or consultants who will only need access for a short period.

In some cases, authentication checks run in the background, evaluating multiple specific risk factors identified by big data analytics. A wide variety of risk factors, identified by big data analytics, combine to create controls to allow or block access to users as required. This increases user session security.

The use of big data analytics to help design and define security measures is also a cost-effective way to expand controlled access to an organization’s virtual private network (VPN). This is particularly useful when working with temporary employees, contractors, or consultants who will only need access for a short period.

Over 30 percent of enterprises will use risk-based authentication to allow remote access by their workforce by the end of 2016, according to a 2013 Gartner report. This is a significant increase over the current figure of less than two percent, and accompanies increasingly complex authentication methods.

As daily business activity is increasingly carried out online either via the internet or through VPNs, authentication becomes a critical part of an organization’s security foundation. Utilizing big data for authentication helps create a highly specific process to best safeguard your organization’s digital information. By doing so, the risk of it falling into the wrong hands decreases exponentially.

Bank’s Use of Big Data and Analytics Holds Key Lessons for Entrepreneurs

big data and analytics
Big Data and Analytics

Uncover new business opportunities with big data and analytics

A growing Utah-based bank is finding new customers and new business opportunities using public records,  big data and analytics.

According to an American Banker article, Zions Bank studies its own transactional data and customer records to find underbanked customer sectors.  By combing through daily transactions, the combination of  analytics and big data help the bank  discover usage patterns and trends within its own customer base.

Data scientists then compare these usage patterns and trends against  publicly available data from government sources like the U.S. Census Bureau, Bureau of Labor Statistics and Department of Labor. And just what does all of this information show?

A goldmine of opportunity –   new markets (including non-bank customers) that could be good opportunities for the small business and consumer banking services that Zions Bank offers within their state.

A quick look at how Zions Bank is using big data and analytics to make marketing and business decisions shows entrepreneurs and startups how to use similar methods to grow their own businesses.

Data Reveals Best Local Areas for Business

Zions uses demographic information to decide which of their branches should offer which services.

After gathering data about factors such as customer education levels, whether customers own homes or rent, and individual or family net worth, analysts reconfigure and plot the data on maps. The maps are then used to target areas for specific products and services based on the demographics of the surrounding neighborhoods. For example, lower-income areas are targeted as being good places to offer check cashing services in the branch, while other branches are chosen for increased small business offerings.

New Target Area or New Product/Service?

Whether you’re running a bricks and mortar business or considering targeting local markets for your digital business, take a look at how Zions tactics could apply to your current customer base. Do the demographics support the services and/or products you offer now? If not, review the demographics of your local market, using publicly available records from municipal, state, or provincial websites or offices. You may find you need to change your target market by location.

Use Big Data and Analytics To ID Customer Segments

According to the article in American Banker, a surprising discovery for Zions Bank was the gap in services provided to Utah’s growing immigrant consumer and business community.

The 2012 census showed that 13.3 percent of the state’s population is Hispanic. At the same time, Utah has a reputation as a state that attracts entrepreneurs.These facts, combined with the entrepreneurial nature of many immigrants, pointed to an opportunity for Zions. Small business banking services for aspiring immigrant entrepreneurs.

“Our mission was to give Hispanic and Asian communities with the opportunity to have banking services and to have more access to capital on the business side,” says Juancarlos Judd, senior vice president of the Salt Lake City–based bank in the magazine article.

Zions provides a solid example of how to use large amounts of  data generated by routine transactions to make better business decisions.  A bank is just one kind of business that is well positioned to harness the power of big data – because they have long been required to keep detailed records of each customer and transaction.

What’ s Hiding In Your Big Data?

Think about your own business.  What kind of useful information could be hiding in your clients’ routine transaction data? This information could help point your business towards a new or revised product,  or a service more suited to the demographics of your client base.

Like Content Quality, Data Quality is King

In today’s automated electronic record keeping environment, gathering data daily results in massive amounts of information. While enterprise businesses often have dedicated data analysts, small and medium-sized businesses increasingly depend on analytics programs to sift through all of this data to find useful patterns and trends. These findings may show areas of both risk and opportunity for businesses.

Zions Bank uses its big data and analytics to discover potential new markets  in the form of overlooked customer segments. The bank  may also have the opportunity to develop new products based on customer activity and demographics, but will  the new markets generate new business? Will the new products meet customer needs?

It all depends on the data quality. Banks have an advantage in this area – they are required by law to update customer records often and collect and keep detailed daily transactions, so it stands to reason their analytics activities will yield useful results.

Keep Better Customer Records

Zions Bank’s  lesson for entrepreneurs is simple.  Keep good records.

Incomplete or incorrect customer profiles, improperly categorized records, and mislabeled files are just some of the problems that lead to inaccurate results when it comes to big data and analytics.

As the financial sector becomes increasingly competitive, the ability of banking institutions to collect and analyze quality data on current and potential customers is proving  an invaluable tool for growth.  The same holds true for businesses of all sizes and across all sectors.  Those that learn to use analytics  with their own big data and publicly available information will be ahead of their competition. And as Zions Bank shows us, there are lessons for businesses big and small when it comes to using big data and analytics to uncover new business opportunities.

Does your business use automated transaction data to find new opportunities? If so, share your best tips in the comments section below.