Big Data and the Future of Healthcare

Big DataBig data has gradually become part of everyday life. From wearable devices and smart phones to vehicles and more, data is collected from just about everywhere and everything. The healthcare industry is slowly coming on board, beginning to use big data in a myriad of ways.

Fraud Prevention

One of the biggest problems in healthcare is fraud. Identity theft, misuse of benefits, and provider payment scams are rapidly increasing, which results in billions of dollars in losses each year. Programs such as Medicare are often the target of such crimes and have taken action by investing in computer systems designed to reduce this hemorrhage of funds. Analytics derived from big data are instrumental in these efforts, able to detect savvy criminals and collusion between patients and providers.

Predicting the Future

Predictive analytics uses big data to foresee the health issues of patients. Information acquired from social media, business networking sites, medical provider visits, family health history, and more are gathered and analyzed. Intricate algorithms assess this data and signal the physician that a medical issue could be oncoming. This advanced notice allows earlier treatment and a much more positive outcome for the patient. In addition, this could help reduce the cost of healthcare by treating patients before they develop a chronic, expensive condition or emergency.

Privacy Concerns

The internet holds a wealth of information that is both public and private. When using predictive analytics to forecast healthcare needs, it is easy to see how privacy is compromised. Private information must be shared with insurers and healthcare providers to truly reap the benefits of the technology. Eventually it may be necessary to create specific privacy laws to help protect patients in this new world.

Other Notes

These programs are still in their infancy, so it’s difficult to know if big data and predictive analytics will ever affect the price of life and health insurance coverage. Current social programs spread expensive claims over a large group of insured patients to attempt to cap premiums. As the political arena changes these programs may as well, making future insurance and healthcare costs difficult to predict.

Big data in healthcare is just beginning to show its power. As technology advances, it’s very likely that this information will be used to save patients and money across the industry. For more information about the future of healthcare IT, contact ROI Networks.

The Impact of Big Data on Education

Big DataAn entire industry has been created around managing, analyzing, and transforming raw data into actionable information. One area where big data has begun to make a perhaps unexpected impact is the education sector. At almost every grade level from kindergarten to graduate programs, educational institutions are discovering the importance of this increasingly valuable asset.

Creating Jobs

The proliferation of big data necessitated an increase in workers with the background to assess and translate files into something understandable and meaningful to organizational leadership. Data analysts, statisticians, architects, stewards, and change agents are all in higher demand as a result of this evolution. Providers of education must develop programs that teach these skills and will accordingly look for trainers, professors, and specialized school administrators who understand data-related careers. They must ensure that growing market needs can be filled by graduates with the appropriate background.

Strategic Planning

When big data is processed and used in purposeful ways, it can have a major impact on the future growth of an organization. Educational institutions are no exception to this. Student results, performance measurements, and retention statistics may be used to assess the effectiveness of a school’s current programs and campaigns. Program gaps and unfulfilled student needs can be identified and corrected. Other subjects could be introduced to attract new students.

Student and Parent Engagement

Keeping the interest of students, especially in earlier grades, can be difficult. These years are critical to the trajectory of a child’s life and the encouragement and involvement of parents is vital. Where big data is instrumental here is in helping to diagnose a child’s stumbling blocks. The school can then convey those details to the parents for assistance and support. The more quickly these obstacles are addressed, the more successful the child may be in overcoming them.

Approaches to Teaching

The performance results that can be obtained via big data are a useful way to tailor teaching methods precisely to each student. Such a high level of personalization improves the outcome of the learning experience. Additional delivery methods such as educational video games and software make learning interactive and fun for youth who might otherwise be disinterested.

Taking the use of big data a step further, some educational software applications use predictive analytics to change lessons to better suit the user. These can identify knowledge gaps as the user works through the content. Such programs are built to accommodate learners of varying skill levels and learning styles so that they absorb knowledge as successfully as possible.

Simplify Student Moves

Historically, if a student transferred to another educational institution, the process of giving the new school their files was cumbersome and time consuming. Big data has made that nearly instantaneous, ensuring that the student and his or her teachers have what they need at the new facility.

Big data is gaining importance across all industries, and education has begun to share in that experience. Through obtaining and assessing student data, the educational experience is enriched. For more information on the role of data in education, contact ROI Networks today.

How Big Data Offers Value to Businesses

shutterstock_134175617The Internet has created a massive ongoing flow of information which can be collected, analyzed, and used to gain competitive advantages and increase business intelligence. Known as “big data,” this informational flow can have a major impact on essential business functions related to customers and products, and on companies themselves.

Big Data and Customers

Big data can be used as a tool for better serving customers and expanding the reach of a business. It helps companies improve their relevance in their respective marketplaces, allowing them to more carefully and precisely target market segments and customer bases with highly evolved strategies. Big data also generates extensive insights into the effectiveness of service delivery models, allowing businesses to make changes to better serve their existing client bases.

Perhaps most importantly, big data also helps companies understand customer purchasing behaviors. Collecting and harvesting information from big data sources provides real-time insights into issues that impact customer behavior and the factors that make it more or less likely that they will choose a particular company, product, or service provider.

Finally, big data can reveal opportunities to move into new markets, or expand a company’s reach in its current markets. Data analysis can help companies identify patterns that suggest new potential sources of revenue — and that’s something every business can benefit from.

Big Data and Products

Big data presents incredible opportunities for companies to personalize their products. Using the data collected during the purchase life cycle can shed light on trends, information, and opportunities that allow businesses to provide a more intimate, customized customer experience, which can lead to improved brand loyalty.

The collection and analysis of data also allows enterprises to improve their service delivery models. Data analytics has created new ways of understanding and adapting to customer needs. For example, airlines like Emirates, Qantas, Delta, British Airways, and others use big data to help passengers with allergies and medical conditions have a more comfortable in-flight experience. Data analytics is also being used to customize loyalty program platforms, using important occasions like customer birthdays to offer incentives and special rates on services.

The launch of a new product is a major event for a business, and big data helps companies track consumer response. This strategy is frequently used in the automotive industry, where car manufacturers use the insights generated by data to make improvements to future models.

Big Data and Businesses

Data analytics can also help companies improve and streamline important decision making processes, including human resource management and the reduction of risks. More and more companies are also using data to better understand employee behavior in the workplace, boosting the efficiency of the internal work flow and helping improve communications between disparate departments and teams.

Big data also helps companies monitor the performance initiatives of their competitors and formulate timely responses to hedge against the possibility of losing ground in market share. It allows companies to counteract advantages gained by competitors, providing a big boost to the bottom line.

Cloud-size Fits All: The Benefit to Small and Medium Enterprises

shutterstock_220352173By now, most have witnessed the power of cloud firsthand. Using this technology for big data and housing applications has become much more commonplace due to its immense scalability and flexible nature.

Despite the growing popularity of cloud, small and medium enterprises (SMEs) are slower to adopt than larger companies. Understanding how this powerful tool can fit into a smaller organization often helps with the decision to migrate.

Cost vs. Benefit

Companies must understand the payoff as well as the implementation process when making technology decisions. Cloud implementation is no exception so the team, along with key stakeholders, should perform a financial analysis to be sure this arrangement is a good fit.

During the cost-benefit analysis, it’s important to remember all of the advantages that cloud-based systems provide. Disaster recovery (DR) is vastly enhanced by this model since it is always on and accessible. This arrangement is an ideal environment for backup and storage of data for the same reason. Redundant hardware and software can be eliminated, saving operational costs. It can improve testing, making development more productive. Cloud arrangements can also be more simple to manage than their traditional counterparts, which reduces the strain on valuable human resources.


One of the most common questions asked about cloud? Whether it is a secure place to store apps and data. The general rule of thumb is never to store sensitive information or code on the public side. That said, a hybrid arrangement of public and private can help reduce costs. General information can be inexpensively stored on the public cloud while sensitive data is hidden on the private side of the platform.

When planning for security in this new world, there are various points that must be included in the strategy. The local area network (LAN), the end-points, and all points from creation to termination and beyond must be locked down. Multiple points of encryption, firewalls, and secure tunnels—like a virtual private network (VPN)—are needed.

Once the pieces of the security puzzle are in place, it’s important that the IT team continues to monitor connections and links. Enforcing server and LAN policies is critical. Intrusion prevention and detection methods are monumentally helpful as part of a comprehensive security strategy. The overall plan should include common best practices as well as industry-specific lockdown or encryption methods.

Cloud allows rapid access to data and applications, making both more usable and effective. Today’s options are becoming more affordable and flexible, which means it is even more accessible for SMEs. Implementing cloud today can certainly provide a competitive edge tomorrow!

The Cloud-y World of Big Data

shutterstock_116697148Two very popular topics of conversation in today’s IT world are the use of cloud computing and the increasing value of Big Data. In the old days, data management meant huge rooms of hardware storing bits and bytes for eventual transmission to an analyst. Those days are far behind as data storage merges with the cloud’s free-form architecture. Using the cloud to process big data in a meaningful way makes sense due to the cloud’s growing list of advantages.

Cloud Perks
Big Data has a natural home in the cloud. Most data traffic in 2015 travels through the cloud already; keeping it there allows more efficient handling of the data. The cloud is quite flexible and accommodating to new requirements, can be expanded or pulled back on the fly, accessed from nearly anywhere and is highly secure if configured properly. In fact, the cloud is often more secure than traditional hardware-based storage since patches and updates are done automatically and in bulk.

A company converting to cloud storage and app management typically enjoys a major reduction in IT costs as well as rarely having to worry about outdated technology. Risks related to data integrity and security are minimized while improving the level of processing and analysis that can be done on the data through the newest data management offerings.

Using cloud computing to handle big data is a no-brainer. Traditional analytics processing requires a lot of overhead whether it be human resource, storage space or bandwidth. Analytics on massive data sets are far more powerful when performed in the cloud because the cloud can be fed from multiple sources and is able to work with data that is completely raw or totally structured. Data results can be ranked in multiple ways depending upon the importance of each data point or data set.

For optimized recordkeeping, separate retention requirements may be assigned to the various pieces of data to simplify regulatory and company records retention policies. This factor lessens the load on the system that could result from storing unnecessary information.

Using a hybrid cloud arrangement in which sensitive data is kept securely in a private cloud while other data can be fed through the public cloud will further lower costs while minimizing the need for hardware resources. Analytics applications can reside in any part or arrangement of the cloud through use of an as-a-service model. AaaS is rising in popularity and has contributed great value to organizations adopting the concept.

Cloud analytics deliver a wealth of real-time information to the stakeholders who need it most, often before they know they need it. Whether the organization is local or global, using Cloud to process and store Big Data lends to an easily governed and controlled data management strategy.