Big data swept by companies integrating the latest digital innovations are now becoming more and more commonplace.
Massive quantities of data are collected from different digital products and platforms, and even smart devices are always connected to the internet. All these gather and transmit detailed information.
It is no wonder that customers are also demanding, in a greater capacity, best practices from companies that collect all this information. Some companies are open about their big data practices, but sadly, some are not.
Some companies choose to conceal in order to control, asking for mercy only when caught red-handed. Industry leaders like Facebook and Google, for instance, have been constantly pushing legal and ethical boundaries when it comes to data privacy.
The biggest scandal Facebook was involved in so far, is the Facebook-Cambridge Analytica Scandal of 2018. Facebook exposed up to 87 million Facebook users’ data to political consulting firm, Cambridge Analytica (shut down since the scandal), who worked on the Trump campaign.
Upon further investigation, Cambridge Analytica employed similar tactics for the Brexit campaign, and other political campaigns they were recently involved with. In all these cases, they were able to optimize the big data they collected from Facebook and other data sources towards their campaign goals.
It is no doubt that the world is now looking at how these big corporations and tech giants are collecting, handling, and using consumer data. Different governments are now coming up with laws to protect data privacy and prosecute guilty parties. Even if a corporation has no current use in collecting and storing private data, transparency and accountability should still be required.
In a world where consumer data is a rising source of competitive advantage, maintaining consumer confidence is crucial. Companies that are upfront about the information they collect, give customers freedom over their data, and provide incentives in return for it will gain consumer trust. These companies will also get continued and even wider access.
For those companies that conceal and control consumer data, also failing to give the appropriate value for it, stand at risk of not just losing consumer trust, but also facing lawsuits and gaining bad reputation.
What is big data?Big data is the process of systematically analyzing, extracting, and managing information from data sets that are too vast and complex to handle with conventional software for data processing.
It refers to the ever changing, enormous and diverse volumes of data garnered from people, machines, tools, social media, smart devices, smartphones and tablets, machine data, video and voice recordings, and structured and unstructured data.
Big data is characterized by the following:
The success of big data is built upon the integration of people, process, technology and information. All these can be incorporated into business routines, strategies, and daily operations.
There is a challenge in sorting through all of the available data to identify trends and information usable for businesses. So, future prediction becomes more important in a business environment that is continually and swiftly evolving.
Challenges of Big Data’s Unprecedented Growth
Big data is definitely revolutionizing the way businesses compete and operate. But as much as big data presents big opportunities, it also presents big challenges.
One of the challenges is that big data is increasingly growing faster than businesses can handle. Currently, consumers produce more data in 10 minutes than all of humanity has ever generated up to this day. Utilization of data has become very competitive between companies.
But big data do help companies gain insights so they can make better, smarter, real-time, fact-based decisions. The market for big data tools and platforms is increasing as the demand for depth of knowledge growth.
Companies continue to strive for advancing their company’s performance through the smart use of big data.
Even the current fight against the Covid-19 pandemic is not just happening with test tubes and beakers, but also with computers and algorithms. Technological health trends are rising, and Microsoft Research engineers, scientists, and programmers are embarking to build applications to help fight against cancer, and big data is going to be crucial in this project.
Emerging technologies will further help companies to enable faster, easier data analysis. Further developments will continue to increase the technical capacity of big data companies to catch up with the ability to capture and store vast amounts of data.
The Impact of Big Data to Businesses
Some of the ways big data are is making an impact with businesses:
Big data removes intuition: Data-driven decisions can be made for areas such as consumer and product profitability, lead generation and retention, strategies for customer satisfaction, marketing segmentation, operations management, performance ratings, and strategies for supply chain and delivery channels.
Big data analytics helps to optimize key processes, functions and roles: Analytics in business is the uncovering and communication of meaningful data patterns businesses can leverage either for growth, profitability, and the like. It is a wide use of data, qualitative and numerical analysis, using descriptive and predictive models to drive fact-based management decisions and actions. Analytics enables organizations to meet demands of stakeholder reporting, handle massive volumes of data, create opportunities in the market, and smartly manage risks, among many others. Businesses that use big data analytics can improve the efficiency and effectiveness of every business decision or action.
Governance: Big data initiatives will fail without good governance in any business. Good governance means clear management in every decision-making with consistent guidance, and transparent procedures. Companies need to make sure that they are protecting all the data exhaustively captured, and share data only with in-built protections and limited access privilege organization.
Management: Organizations must begin to manage data from various sources and integrate their usefulness into the market via a number of technologies. Some estimates indicate that over 80 percent of the data in organizations are unstructured and unsuitable for traditional treatment. Big data will enable processing of this unstructured data and increased system intelligence. It can be used to improve sales performance, increase understanding of customer needs, strengthen function of internal risk management, support marketing campaigns, and enhance fraud monitoring.
Usage: Merging data and processing power helps unlock big data 's potential. This is good news for various sectors and industries. The major obstacle is the capacity to analyze the huge amount of data that can be collected from different sources.
Quality: Data quality is becoming ever more critical and companies need to create effective functions and criteria for big data. Correcting errors are costly and disastrous, so it is important to get data right at the onset. For instance, how crucial it is for the healthcare industry to gather and process data accurately. Big data is opening new frontiers in medical technology, like the integration of databases for disease, tissue, and genome. Big data is defining key approaches in medical care. Big data needs to be handled with utmost care to preserve its quality and integrity.
Security: Security is one of the top considerations with big data. Companies and tech giants are consolidating sensitive data with bigger data. Security policies need to be in place and must be self configurable, and optimized. Smartphone and wearable technology has multiplied app development. In turn, it is multiplying the data being gathered at massive amounts at a time. It puts consumers and companies at risk, so maintaining security over data collection, data management, data usage, and data exchange must build and preserve consumer trust.
Privacy: The increased usage of big data is unraveling traditional security frameworks for data privacy. Companies must audit the implementation of these privacy policies at all times, across all digital products and frameworks they employ. For instance, automobiles have become complex mobile platforms that employ a plethora of digital products and services like computers, sensors, GPS, IoT, and more. There needs to be protocols set by automobile companies so that any data collected and transmitted remains secure and uncompromising. Customers must not be kept in the dark regarding big data, especially how their personal data is collected, and how much data is being taken from them. But sadly, not all companies have the integrity to do this. Some construct covert activities in the effort to control data beyond the consumer’s knowledge and permission.
Privacy: The increased usage of big data is unraveling traditional security frameworks for data privacy. Companies must audit the implementation of these privacy policies at all times, across all digital products and frameworks they employ. For instance, automobiles have become complex mobile platforms that employ a plethora of digital products and services like computers, sensors, GPS, IoT, and more. There needs to be protocols set by automobile companies so that any data collected and transmitted remains secure and uncompromising. Customers must not be kept in the dark regarding big data, especially how their personal data is collected, and how much data is being taken from them. But sadly, not all companies have the integrity to do this. Some construct covert activities in the effort to control data beyond the consumer’s knowledge and permission. Data sharing is inevitable, and can add value to people’s lives through the products and services that can be produced from data sharing. Indeed, the progress and adoption of products that optimize personal data keep rising. In fact, Gartner says that there will be close to 25 billion connected “things” by 2020. It is therefore a requisite for data privacy laws and guidelines be set in place to guide the development of this technology towards protecting the rights of people to data privacy, preservation, and freedom.
Trust and Transparency: Studies show that transparency about data usage and preservation reinforces consumer trust. Trustworthiness is a major factor for consumers. If consumers find a company untrustworthy, collection of any or certain types of data will be a challenge. Trustworthy companies, on the other hand, need only to ask. Trust is a foundation that needs to be built and nurtured, despite the ever-growing market. It is that one constant thing that must be upheld. Most often, there's no turning back once you have broken consumer trust.
How to Create a Foundation of Trust
Best Practices and Enlightened Data Principles: trust-building must be first and foremost in this process. Even the tech industry's biggest names, like Facebook, Google, Apple and Microsoft have had to reassess big data management and resolve any handicap.
Companies must include data privacy and security into the development of products and services.
Consumer Education: Companies need to take time in educating their consumers about their data, how it is collected, what is being collected, what data will be protected and managed.
Give control to data owners: Consumers must have freedom and control over their data. Data collection must never be forced, or worse, beyond the consumer’s knowing. Consumer-directed data collection and management is imperative if we were to preserve their trust and continue data collection and analysis.
Deliver great value: Businesses do not have to force or pay users for. If your consumers trust you, they will provide the data you need to give them the best possible service. But companies do need to deliver great value to their users. For instance, Pandora is a music service built on this principle. It gathers self-reported data in a clear and transparent manner. Customers willingly provide their details during sign up and through usage of Pandora’s service.
Conclusion: Build Trust as a foundation for Big Data Services to thrive upon
Many companies are actively exploring new possibilities to create new revenue streams. Monetizing shareable data is one of them. In fact, it is one of the major business strategies as big data industries grow. But companies must not lose sight of protecting their consumers, adding significant value, providing personalized experiences, and not breaking consumer trust. The Data-as-a-Service (DaaS) market will continue to progress as the list of third-party data providers utilized by various companies also increases. But as trends grow, It is crucial to consider what data is shared, how it is shared, and why it is being used. New business models must be enacted to incorporate big data, AI, machine learning, and IoT services that do need data governance and accountability. Trust is like a lasting investment and a growing competitive edge for companies employing big data. Give your customers assurance regarding their privacy. Stay transparent, ethical, value driven, and consumer-driven.