big data and 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!

Enterprise Technology Solutions Leader, Exist Reveals Top 5 IT Trends for 2019

Enterprise Technology Solutions Leader, Exist Reveals Top 5 IT Trends for 2019 768 487 Exist Software Labs

The demand for business companies to go digital continues as they face the new year with new expectations, competitors, channels, threats, and opportunities. Digitalization has created a new breed of market that companies of all sizes- small, medium-sized or even large corporations cannot ignore. Traditional businesses have now accepted using digital transformation as a business strategy— to deliver products and services through web, reap data from every market interaction then gain insights to rapidly optimize their value chain and help them increase competitive advantage.

By transforming digitally, businesses are able to build a connection with their customers, speed up the pace of innovation and, as a result, claim a greater share of profit. Today, companies that invest in digital transformation are building an edge over those who don’t, that will enable them to succeed in reaching the expanding digital lives of consumers that encompass the rules of engagement that strongly influence customer loyalty.

With this profound effect on business organizations, allow us to share what are the IT Trends our top executives think would make an impact by the year 2019:

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Blockchain

By allowing digital information to be distributed but with a highly secured transaction, blockchain technology created the backbone of the new type of Internet. What do we really mean when we say blockchain? According to Don and Alex Tapscott, authors of the book Blockchain Revolution (2016), “the blockchain is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value”. The growing list of records found in blockchain is called blocks which are linked using cryptography.

In an interview with Mr. Mike Lim, President & CEO of Exist, he stated, “blockchain has been really gaining quick traction not only because of bitcoin or cryptocurrency but because of the promise of more transparent but secured communication between B2B companies or even B2C depending on what vertical you are.” Blockchain gives internet users the ability to create value and authenticates digital information. By storing data across its peer-to-peer network, blockchain eliminates a number of risks that come with data being held centrally. Every network participant validates the transaction so that the data stored is immutable and cannot be forged.

Real-world applications of blockchain technology are becoming more mainstream resulting in the amount of transactional data to become huge. Combining blockchain and big data sparks a new level of analytics. Executives believe that the blockchain promise of secure, traceable transactions and improved transparency of information can streamline supply chain management. Thus, continuing to make a disruptive change in technology by the year 2019.

 

Big Data

With today’s digital technologies, it’s possible to analyze your data and turn it to insights rapidly, enabling enterprises to make better decisions.

According to Gartner, big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation. As the head of the healthcare services at Exist and the VP for Sales and Marketing, Mr. Willex Perez shared to us his thoughts: “Imagine the possibilities of what big data can do for predicting illnesses. If you collect enough clinical information you’ll be able to compare your status or your clinical values with others. After which, you can search available research or studies to check your risk rating as an individual.”

Emphasizing on healthcare, Mr. Willex added that among the growth trends the use of big data in healthcare will be essential. “With analytics, enterprises will be able to drive innovation and come up with intelligent business decisions. While organizations collect data for analytics purposes combined with IoT as another major source for data,” Mr. Willex concludes, “it is inevitable to use big data analytics to complete the picture.”

 

Internet of Things (IoT)

Countless business opportunities are in the fire hose of IoT data as products and services have become more connected. Internet of things refers to the network of devices such as home appliances, mechanical and digital devices that contain electronics, software, and connectivity which allows them to interact and exchange data.

Considered as one of his top IT trends, Mr. Christopher Silerio, the VP for Operations at Exist, believes IoT sensors provide us a valuable real-time update of the exchange of data with the sources. He shares, “there will be a time when there will be more data exchanges happening between sensors even without human interaction.  From smart appliances or smart meters, devices will continuously send data signals to a certain component or machine, providing information in real time. It’s reasonable to say that IoT has begun to transform the business landscape and is expected to continue in 2019.”

 

Cloud

While IoT generates huge amounts of data, the cloud ensures that these are captured and stored properly. The simplicity and accessibility of cloud computing to manage vast amounts of data remain a catalyst enabling the rapid expansion of IoT. Cloud computing provides small to medium enterprises the ability to enjoy low implementation cost for their total IT infrastructure and software systems.

Utilizing the abilities of cloud computing, enterprises of all sizes can deploy applications a lot quicker and cheaper compared to the cost of setting up whole IT Infrastructure and service by themselves. According to Forrester’s predictions for 2018, the total global public cloud market will be $178B in 2018, up from $146B in 2017, and will continue to grow at a 22% compound annual growth rate. From this perspective, the cloud seems to be a key driver of digital transformation and economic growth.

“Cloud makes it easier for organizations to worry more about their business process rather than infrastructures. It makes it easier for startups to build their business quickly,” reveals Mr. Jonas Lim, the VP for Technical Services at Exist. “As early as almost a decade ago, we believed that cloud computing is a real game-changer and it has proven to be true as the future continues to bring us into a world of unlimited connectivity empowered by the cloud,” he further adds.

 

Artificial Intelligence

Artificial intelligence or AI doesn’t only apply to robotics. As a branch of computer science, AI involves the development of computer programs to complete tasks which would otherwise require human intelligence. As evidence of its spread, AI is even available for use along with other cloud solutions by which businesses can just subscribe to.

Internet technology companies also make use of  AI to optimize their IT infrastructures. In fact, according to Wikibon: “AI-optimized application infrastructure is one of today’s hottest trends in the IT business. More vendors are introducing IT platforms that accelerate and automate AI workloads through pre-built combinations of storage, compute, and interconnect resources.”

Mr. Jonas Lim pointed out the increasing use of chatbots in business services. Chatbots are programs built to automatically engage with received messages simulating actual human interaction. In addition, artificial intelligence might just be ready to explode with its use, particularly inside the healthcare industry.

What started with manufacturing has now spread to knock and open the doors to greater digital business scale but now with analytics and computing intelligence at the forefront of cutting-edge changes in the upcoming years. “[Like] growing population of robotics is bound to happen,” Mr. Willex added, “and although we don’t know the future, it is quite evident that interacting with AI will soon be part of our everyday lives.”

Don’t Get Wiped Out Riding the Big Data Wave: Hang Ten with Informatica Big Data Management

Don’t Get Wiped Out Riding the Big Data Wave: Hang Ten with Informatica Big Data Management 768 487 Exist Software Labs

Data has always been the key factor in business computing. However, the role that it plays has evolved throughout the years. These evolutionary epochs have generally been termed as the 3 waves of data management.

Wave 1: The Rise of Relational

In the first wave, we see the emergence of the relational model and relational database management systems as an improvement upon the flat file data store. Having the advantage of a structured query language (SQL) to extract data from the database enabled businesses to more easily derive value from their data.

Data in this era was used to support specific business processes and applications.

Data served the application.

Wave 2: Eyeing the Enterprise

The second wave will have data being used in a more enterprise-wide fashion. Here we see the emergence of the use of unstructured data in the form of documents, web content, images, audio, and video in Enterprise Content Management (ERM) systems. Other applications would be Enterprise Resource Planning (ERP), supply chain, etc.

Data served the enterprise.

Wave 3: The Tsunami of Data

We are currently in the 3rd wave. Vast improvements in cost efficiencies in the areas of storage, network speed/reliability, memory, and over-all computing capability have paved the way for the emergence of Big Data.

Simply put, Big Data is the ability to gather very large amounts of all kinds of available data (structured, semi-structured, unstructured) at various latencies (even real-time), profile the data, catalog the data, and parse/prepare the data for analysis, all done in a distributed file and processing architecture.

Data in the 3rd wave is front and center. It now transforms business processes (see Wave 1) and creates new business models (see Wave 2).

Data powers digital transformation.

 

Wipeout Points with Big Data

The following are some pain (wipeout) points with Big Data:

1. Functionality and performance gaps of processing engines on Hadoop – These frameworks (such as MapReduce, Hive on Tez, and Spark) are good for certain use cases but lack the core functional and performance requirements for big data integration.

2. Provide faster and flexible development – a big data journey should be lean and agile, focusing on automation, reusability, and data flow optimization.

3. Search data assets in Hadoop and the Enterprise – a solution that enables easy searching and discovery of relevant data sets is not readily available. There is the need to answer the question: How do I find my data and know their relationships?

 

Ride the Wave with Informatica

It must be noted that Informatica has been the leader in data management in Wave 1 and Wave 2.

With Wave 1, Informatica pioneered and defined ETL and data integration categories. They are still the market leader in these areas.

With Wave 2, as data became enterprise-wide, Informatica added data quality, master data management, cloud integration, data masking, and data archiving to their solution portfolio. They are the market leader in each of these categories.

Hanging Ten with Informatica Big Data Management

Hadoop Ecosystem

With the arrival of YARN, the capability to build custom application frameworks on top of Hadoop to support multiple processing models was realized. What Informatica Big Data Management (BDM) did was combine the best of open source (i.e., YARN) and 23 years of data management experience to build out Informatica Blaze.

So what is Blaze? You can look at Blaze as a cluster-aware, data integration engine for Hadoop—built using in-memory algorithms, all in C++—for Big Data batch processing. It’s integrated with YARN, so you can expect it to be a very scalable and very fast, high-performance distributed processing engine for Hadoop.

But does Blaze replace the other Big Data processing engine frameworks? Does it replace MapReduce, Tez, or Spark? The answer is No. What Blaze does is actually complement the capabilities of the other processing engines by virtue of the fact that there is not one solution to solve all of the Big Data batch processing use cases.

What Informatica did to overcome the functional gaps of the other processing engines was expose their transformation libraries (built over 23 years) to the Hadoop ecosystem—to a distributed processing platform—through the Informatica Blaze engine. What that allowed Informatica to do was open the floodgates to a lot of their functionality (not just the core functionality of joiner transformations, aggregates, and look-ups, but also their complex data integration transformations: the complex data quality, data profiling, and data masking transformations) through the Blaze engine, making it much easier for you to implement complex ETL processing in a Hadoop ecosystem. In terms of performance, what Informatica did was they took Blaze and made it an in-memory processing engine built purely on C++.

If I execute a mapping on the Hadoop cluster, you may be wondering, will it automatically default to the Blaze engine? Not necessarily. Informatica BDM has this key innovation for the Hadoop ecosystem called the Smart Executor. It’s a polyglot engine. This means that it has the ability to understand multiple languages and implies that not one technology will solve all the Big Data integration use cases. What it does is it automatically, dynamically, and intelligently selects the best execution engine to process the data based on various parameters like mapping, workload type, and infrastructure configuration. It will optimize that mapping and, based on the cluster configuration, determine which is the best execution engine to run it on and could pick either of the engines as faster than the others. It is built to intelligently pick the best execution engine.

Informatica Blaze

As the graph above indicates, Informatica Blaze is faster than Spark and Hive on MapReduce. But why?

With its multi-tenant architecture, Blaze allows you to run concurrent jobs served by one single Blaze instance. This translates to optimized resource utilization and sharing amongst jobs. So even if you have a thousand mappings for execution, Blaze will only launch one YARN application to serve this requirement. Also, as mentioned earlier, Blaze was written in C++ code, providing better memory management compared to a Java-written framework.

Blaze also uses the Data Exchange Framework (DEF), a process for the shuffle phase, which is an in-memory built framework that shuffles data amongst the nodes without the loss of recovery—a very key capability in Big Data processing for Big Data processing engines.

 

Safely Back to Shore

What your business does with data will determine whether it will wipe out and sink to the bottom or ride the wave all the way back to shore.

With Informatica and Informatica Big Data Management, you can be assured that your data will be made to drive the digital transformation needed to ensure that your business is empowered and not floundering around.

 

 

 

References:
1. Module 04: Informatica BLAZE Overview: Big Data 10.x: Black Belt Enablement (Module) (internal partner resource)

2. Keynote: CEO Anil Chakravarthy – Informatica World 2016 )

3. Big Data for Dummies by Judith Hurwitz, Alan Nugent, Dr. Fern Halper, and Marcia Kaufman (Hoboken, NJ: John Wiley & Sons, Inc, 2013) (https://www.amazon.com/Big-Data-Dummies-Judith-Hurwitz/dp/1118504224)