data analytics

The 7 Wonders of Big Data and Analytics in the Power and Energy Sector

The 7 Wonders of Big Data and Analytics in the Power and Energy Sector 768 487 Exist Software Labs

Big data and analytics help the power and energy companies address and overcome new industry challenges through insights-based informed decision-making.

Nothing is forever. Like oil and gas, our natural energy sources are on the brink of scarcity, but global energy consumption is growing each fleeting day. The only way to earn extra time is to optimize its use correctly or gradually shift to renewable energy. To do that, big data and analytics help in automating and digitizing production, demand, and supply.

What is big data and analytics, you ask? IBM defines big data as any data that cannot be captured, managed, and/or processed by traditional management components and techniques. While analytics uses advanced mathematical techniques on diverse big data sets from different sources and in various sizes. In other words, data becomes big data when traditional methods, or a single computer, cannot be used to deal with data. It becomes analytics when these big data sets are processed.

The power and energy sector produces and collects large data sets continuously over some time. This data comes from their technology infrastructure, including sensors, cloud computing, wireless, and network communication. Smart meters alone in about a million households can collect 200 terabytes per minute.

Competitive edge of Big Data and Analytics

Businesses across the power and energy industry face many challenges to manage this data and draw insights from it. But when they start to invest in big data and analytics, data-driven companies will cultivate benefits in the long run. So, let’s look at the seven biggest advantages of implementing a big data strategy for power and energy companies.

1. Energy Efficiency

Energy preservation has always been a global issue. While there are advancements in using renewable and reusable energy, necessity still lies in saving it. But in today’s scene, companies should look more into using energy efficiently, requiring less energy for the same function, which is possible with technology.

By 2035, the Asia-Pacific Economic Cooperation (APEC), in which the Philippines actively participate, targets a reduction of aggregate energy intensity by 45%, based on 2005.

Big data analytics can play a significant part in the power sector’s role in this situation by deriving data coming from smart meters, asset operations, business policies, and weather data. It can be integrated and analyzed over time, which helps design electrical devices with energy-efficiency parameters, thus reducing power requirements. Energy efficiency plays a vital role in reducing carbon emissions. To achieve this, power corporations can forecast usage and predict savings by leveraging big data solutions in this manner.

2. Risk Management

Implementing a big data strategy in any business model can work wonders in assessing and managing hefty risks. It eliminates the practice of deriving business decisions from gut-feel and empowers executives with hard evidence instead. The truth can be said for the power and utility industry. Making informed investment decisions is the pinnacle of effectively utilizing the power of big data analytics.

Energy companies can derive valuable insights from power generation and consumer consumption. Predicting anticipated prices, creating dynamic pricing based on peak usage and demand, and adjusting the business operation model to cope with challenges can be done with data-driven decision-making. Enterprises that can embrace big data solutions’ advantages will have a strong market position and attain sustainable business growth.

3. Power Planning

Coming up with optimized power generation planning is another significant benefit of a big data analytics strategy. The strenuous task of matching power supply with the demand for energy on the grid, or economic load dispatch, can be performed quickly and efficiently by applying advanced big data analytics techniques. In effect, it improves energy production efficiency and lowers production costs.

4. Data Collaboration

Understanding what problems to address is first and foremost before implementing an analytics strategy. Big data analytics can predict production demand in the power sector, enhance efficiency, and optimize the operation process. Whatever it may be, enterprises can work with a wide range of data. Bringing all this data together can take a lot of time, but using big data analytics tools to collaborate all data can streamline the process and present visualized reports. 

5. Supply Chain Visibility

The retail industry utilizes big data effectively, especially in managing its inventory and forecast demand to improve supply chain management. The power sector is no different from retailers with its utilities. Technologies today, such as smart meters and smart grids, integrate with big data systems. This strategy enables enterprises to balance demand and supply, facilitate dispatch decisions, increase efficiency, organize inventory, and enhance reliability.

6. Customer Engagement

It is of vital importance for energy companies to be a data-driven and customer-centric business. Technology advancements, government regulations, and shifting customer behavior fast-track an optimized plan for consumer engagement. With big data analytics implementation, energy companies can shift to engage with customers in highly personalized environments, which can increase customer satisfaction, promote new products and lower the service cost.

7. Predictive Maintenance

Logical algorithms can consolidate and assess a large volume of data for power companies, enabling them to develop more effective business strategies. Energy providers can respond quickly in near real-time by predicting the market using specified vital indicators. Implementing big data will improve equipment monitoring and maintenance that will minimize production hours and system disruptions.

Transformation through Big Data and Analytics

With innovations such as predictive analysis, the power and energy industry is experiencing a large-scale transformation. With the assistance of predictive analysis, grids and meters are becoming more intelligent.

It is more evident today than before that this sector has a vital role to play in delivering essential products and services necessary to the world’s economy. Regardless of the industry’s shifts, power providers should continue to satisfy essential standards to provide energy services that are efficient, accessible, and sustainable.

Businesses continue to grow each day, but there are so many out there who do not have this technology and are not experiencing its benefits. There are real-time predictive analytics, grid operations analytics, and consumer analytics that power and energy providers can invest in.

Investment is mission-critical in this scenario to reap the real benefits of big data and analytics. Each day offers new opportunities, and the best solutions to today’s problems are yet to be done. The new normal calls for new innovations, and it is prime time for the power and energy sector to embrace this idea fully.

Exist is your data solutions partner of choice!

Explore the next level of your digital transformation journey with big data and analytics. Let’s look at opportunities to better maximize your ROI by turning your data into actionable intelligence. Connect with us today, and we’ll proudly collaborate with you!

Asia-Pacific: Fastest Growing Market in Big Data Analytics

Asia-Pacific: Fastest Growing Market in Big Data Analytics 768 487 Exist Software Labs

At a time when the pandemic forced enterprises to cut-down ICT investments, there remains optimism in anchoring big data analytics to improve business performance and derive highly informed business decisions.

About 3 in 4 enterprises in Asia-Pacific choose to keep investments in big data analytics (BDA) solutions or even expand this year, according to the latest COVID-19 survey by IDC. This standpoint is sound for businesses as big data analytics presents proven and essential use in enabling digital trust and resiliency now and post-pandemic, more so.

The coronavirus pandemic has caused a decline in the number of ICT investments. But businesses see technology resiliency as the best way to oppose its negative impact. By gathering relevant insights, enhancing productivity, satisfying customers, recognizing fraud, and reducing expenses, enterprises remain competitive with a data strategy in place. Moreover, enterprises are pushing towards public cloud deployments to optimize BDA investments.

The positive outlook around big data analytics comes at a time when global crisis forced companies to cut ICT expenditures. This decision became almost instinctive because of big data analytics’ proven value in keeping businesses alive amid the pandemic.

Energy sector’s fastest-growing market

In a report published by Mordor Intelligence, the Asia-Pacific (APAC) shows a promising future leading the energy sector’s market growth in big data analytics. The market intelligence and advisory firm cited the increased adoption and demand for IoT and smart technologies in government initiatives across the region.

If there is one thing that the energy sector can reap benefits from big data analytics, it is the power to manage scarce resources. After all, only 5% of the world’s energy consumption comes from renewable sources.

The most remarkable technology that is most likely to boost the market growth in 2021-2026 are smart meter systems. Smart metering in big data analytics involves components, such as grid operations, field services, resource planning, customer experience, and regulatory compliances. Big data analytics in smart metering helps in predicting energy consumption. Clearly, this empowers enterprises in managing supply and demand, and mitigating energy waste.

The same report mentioned India’s growing deployment of almost 2 million smart meters. Which takes advantage of today’s technologies and big data techniques. At the same time, China will be the leading country. Due to its increasing adoption rate of smart meters and smart grids across the country with its large population.

Banks and Telcos leading the pack

Contributing to nearly one-third of spending on big data analytics in the APAC region for 2020-2024, banks and telcos are the top verticals investing in BDA solutions: a report published by the technology research firm IDC.

Capitalizing on financial, transactional, and customer data, the banking industry has always been a haven for big data analytics and will remain so in the foreseeable future. With customers shifting to a more digital experience in banking, bank providers are pushing to scale up their digital transformation as rightfully so. Even though considering complicated legacy banking systems as a hurdle, bank executives recognize prioritizing digital initiatives.

Relatively, the telco industry shows a promising position as the second most prominent investor in big data analytics. Telcos leverage data on customers, sales, and marketing to gain insights for business growth. As we have mentioned before, big data analytics can help optimize the customer experience, which is a big thing for this sector.

State of big data analytics in the Philippines

In Southeast Asia, the Philippines is one of the fastest-growing economies in the region. The country’s expected annual GDP growth surpasses the 5.3% regional average, which stands at a solid 6%. Despite this, competition continues to grow as more digital innovations disrupt traditional business models. Data is everywhere and is becoming more available than ever before. Businesses should see this with a bird’s eye view of how big data can translate to business value. At the same time, customers are engaging with highly personalized experiences.

The Philippines market for big data is still very small. If large firms continue to embrace BDA services and recognize worth, small and medium businesses will follow. This is, however, with a condition. A robust legal framework and support from the government must be in place. Especially, data privacy and security remain to be of major concern.

Optimism in anchoring big data analytics

The big data scene can create around 10 million new jobs in the next five years, Former Globe Telecom chief information officer Henry Aguda shared in an interview with Rappler. If this outlook proves itself, this can directly impact the state of the country’s economy and provide employment opportunities.

Besides employment, possessing hardcore evidence-backed decisions can only do good and be a superpower for firms and organizations. With big data utilized to develop more rigid solutions, businesses can be proactive on what the market wants. In this case, an opportunity is on the rise: tweaking products and services by attending to consumer habits.

Companies worldwide have already established that deeper assimilation and application of data analytics in business translates into greater business value. It is becoming more evident here in the Asia-Pacific region, with enterprises increasing their investment in advanced toots and infrastructure to manage their data better. In this way, companies are taking the right path. A new level of innovation in an increasingly competitive global market.

Exist is your data solutions partner of choice!

Explore the next level of your digital transformation journey with big data and analytics. Let’s look at opportunities to better maximize your ROI by turning your data into actionable intelligence. Connect with us today, and we’ll proudly collaborate with you!

4 Proven Ways Data Analytics Increases Revenue

4 Proven Ways Data Analytics Increases Revenue 768 487 Exist Software Labs

With great data analytics comes great returns.

In this day and age, the influx of data has overwhelmed businesses. Which prevents them from maximizing the potential of big data analytics to drive even more revenue and profit. Forbes shares that there are 2.5 quintillion bytes of data created each day but only 0.5% is analyzed.

In the Philippines, only two out of five companies are highly data-driven. But a good thing to note, most Filipino businesses realize this as an advantage. With three out of five having data and analytics (D&A) teams. (PwC Data Analytics Assessment and Readiness Survey, 2020)

We should know by now that making business decisions based on hard evidence from data is becoming a competency and an edge for those who utilize it. Case in point, the McKinsey Global Institute indicates that data-driven organizations are 23 times more likely to acquire customers, six times as likely to retain those customers, and 19 times as likely to be profitable as a result.

Today, getting the most value out of your data is a superpower that business leaders should invest in. It is a profit-increasing ability based on facts, trends, and statistics rather than a gut feel.

In this blog, we’ll share with you four proven ways that embedding a clear data analytics strategy into your business can maximize your returns.

#1. Improving processes to reduce errors

One of the best benefits of having effective data analytics in your business is improving your processes to reduce wasted money and time. 

For instance, you’re in a bread manufacturing company struggling to predict the right numbers to make in a day. In effect, your company overproduces and ends up with wasted unsold food as it expires in less than a week. Besides that, you want your product as fresh as possible when it goes straight to supermarket shelves.

This is where data analytics comes to play. As a result, you can make more accurate forecasting of the demand and supply. Which can significantly reduce the percentage of loss or waste and increase profitability.

#2. Mapping business performance

Another advantage of utilizing data analytics is data visualization. The power to see how your business performs gives you a clearer picture of your goals and targets.

With the right tools to visualize your company data, you’ll be able to map employee performance, team outcomes, company goals, and quarter results, among others. In other words, this empowers your business to look at rooms for improvement and opportunities to consider.

For sure, presenting numbers and graphs has always been a part of your business reviews. That’s why with the right tool, you can also reduce working hours spent on creating manual reports and data consolidation by automating reports generation. Now, your staff can spend valuable time on more critical operational business tasks.

#3. Optimizing the customer experience

Undeniably, the behavior of customers is becoming a lot clearer and available today. You can gather lots of data from various consumer touchpoints. Such as your company website, social media presence, and electronic payments.

After identifying these touchpoints, data analytics can help you optimize the customer experience. Likewise, businesses can harness data to find new customers, track social media interaction with the brand, improve customer retention rate, capture customer inclinations and market trends, predict sales trends, and improve brand experience.

Using the right data can help you plan out an effective marketing strategy and know when to launch your new products and sales. Data is your lens to interact seamlessly with the right customers at the right time.

#4. Getting ahead of the competition

I can’t stress this enough: there’s a multitude of ways your business can utilize your data. So, using this ability to get ahead of your competition is untapped power.

Firstly, data analytics can identify the best channels for your business that offer more significant ROI and focus on them. It will be a driving force to develop a better, informed marketing and sales strategy by analyzing trends and insights from gathered data. You can even avoid spending thousands on marketing campaigns that don’t even address your target audience.

Another one, analyzing data can reveal what your market needs and wants. Keywords can tell you exactly what features your customers are searching. From its frequency, you can infer the relevant priorities of opposing interests. While the relative change can identify and predict trends in customer behavior. It can even understand where customers are struggling the most and how support should be stationed.

Data Analytics empowers Businesses of the Now

Knowing these ways to embed data is just a starting point. If companies can exploit the potential of big data analytics, they can dodge being a business of the past.

Data and analytics are the key forces to an organization’s digital transformation. That’s why Gartner predicts that by 2022, about 90% of corporate strategies will explicitly state data as a significant asset and analytics as a competency.

That’s quite of an outlook. To reiterate: With great data analytics comes great returns.

In a study of over 400 businesses by Bain & Company, they found out that those with the most advanced data analytics get a larger market share. Moreover, they were twice as likely to be in their industry’s top 25% for profitability and five times more likely to make faster decisions than competitors.

Therefore, we can’t ignore the fact that the world’s data production is accelerating. Its effect on the business landscape is getting more and more realized. And being able to derive business decisions from hardcore data analytics is a power that yields better outcomes.

Exist is your data solutions partner of choice!

Explore the next level of your digital transformation journey with big data and analytics. Let’s look at opportunities to better maximize your ROI by turning your data into actionable intelligence. Connect with us today, and we’ll proudly collaborate with you!

Befriending Your Data in 2021

Befriending Your Data in 2021 768 487 Exist Software Labs

It’s the new year and everybody is still living in the wake of the COVID-19 pandemic. We all need a friend in times of trouble and this is no different in the case of business organizations.

This year, 2021, the friend that your company needs more than ever, especially in these trying times, is data. Given the disruption that this virus caused in the preceding year, enterprises need to start (if they haven’t already) befriending their own internal data, and perhaps external data as well, if they are to at least stay viable and at most grow.

The following are some insights from respected data management leaders on how to make friends with your data this year:

  • “Data warehouses are not going to disappear. Data warehouses will continue to be an important legacy technology that organizations will use for mission-critical business application well into the future. With the transition to the cloud, data warehouses got a fresh new look and offer some modern attractive capabilities including self-service and serverless. With the rise of the cloud, data lakes are the new kid on the block. Data lakes are becoming a commodity, legacy technology in their own right. Their rapid emergence from the innovation stage means two things going forward.

    First, organizations will demand simpler, easier to manage, and more cost-effective means of extracting usable business intelligence from their data lakes, using as many data sources as possible. Second, those same organizations will want the above benefit to be delivered via tools that do not lock them into proprietary data management platforms. In short, 2021 will begin to see the rapid introduction and evolution of tools that allow users to keep their data lakes in one place and under their control while driving performance up and cost down.”

  • “Distributed analytical databases and affordable scalable storage are merging into a single new thing called either a unified analytics warehouse or a data lake house depending on who you’re talking to. Data lake vendors are scrambling to add ACID capabilities, improve SQL performance, add governance, resource management, security, lineage, all the things that data warehouse vendors have been perfecting for the last three or four decades. During the ten years, while data lake software has been coalescing, analytical databases have seen their benefits and added them to their existing stacks: unlimited scale, support for widely varied data types, fast ingestion of streaming data, schema-on-read, and machine learning capabilities. Just like a lot of things used to claim to be cloudy before they really were, some vendors will claim to be a unified analytics warehouse when they’ve just jammed the two architectures together into a complicated mess, but everyone is racing to make it happen for real. I think the data warehouse vendors have an unbeatable head start because building a solid, dependable analytical database like Vertica can take ten years or more alone. The data lake vendors have only been around about ten years, and are scrambling to play catch-up.”

  • “One single SQL query for all data workloads

    The way forward is based not only on automation, but also on how quickly and widely you can make your analytics accessible and shareable. Analytics gives you a clear direction of what your next steps should be to keep customers and employees happy, and even save lives. Managing your data is no longer a luxury, but a necessity–and determines how successful you or your company will be. If you can remove complexity or cost of managing data, you’ll be very effective. Ultimately, the winner of the space will take the complexity and cost out of data management, and workloads will be unified so you can write one single SQL query to manage and access all workloads across multiple data residencies.”

  • “Expect more enterprises to declare the battle between data lakes and data warehouses over in 2021 – and focus on driving outcomes and modernizing.

    Data warehouses can continue to support reporting and business intelligence, while modern cloud data lakes support all analytics, AI and ML enablement far more flexibly, scalably, and inexpensively than ever – so enterprises can go transform quickly.

    Cloud migrations and related cloud data lake implementations will get demonstrably faster and easier as DIY approaches are replaced by turnkey SaaS platforms. Such solutions will slash production cloud data lake deployment times from months to minutes, while controlling costs and providing the continuous operations, security and compliance, AI and ML enablement, and self-service access required for modern analytics initiatives. That means that migrations that used to take 9-12+ months are complete in a fraction of the time.”

  • “Co-locating analytics and operational data results in faster data processing to accelerate actionable insights and response times for time-sensitive applications such as dynamic pricing, hyper-personalized recommendations, real-time fraud and risk analysis, business process optimization, predictive maintenance, and more.

    To successfully deploy analytics and ML in production, a more efficient Data Architecture will be deployed, combining OLTP (CRM, ERP, billing, etc.) with OLAP (data lake, data warehouse, BI, etc.) systems with the ability to build the feature vector more quickly, and with more data for accurate, timely results.”

To summarize the various points made by these industry pundits:

1

SQL-driven data warehouses are here to stay and will continue to be the data analytics platform of choice for enterprises in the current year.

2

Data management platforms that integrate well with existing data lakes will dominate as opposed to platforms that focus on one or the other.

3

Data management platforms that have built-in AI/ML functionalities will dominate as well, as this eliminates the cost and complexity of separate AI/ML analytics platforms.

4

Data management platforms that are cloud-ready will also have an edge over those that are not.

Is there a data management platform that possesses all these qualities and has a proven track record in Fortune 500 companies?

Yes, there is. It’s called Greenplum. Read about it here.