Top 7 Data Related Predictions for 2017 – Part 1 of 2
February 27, 2017
In the world of business and consumerism, data footprints are everywhere. The moment consumers purchase an item from an e-commerce site alone is data regardless of whether it was done anonymously or through a registered account. To cite some examples: Airlines track passenger data, Utility firms record subscribers and utilization, Media companies track content viewership, and Logistics providers track delivery route data.
Most companies record data to process them and gain insights to improve their products and services. The challenge lies in understanding how to best process the data using available and more modern technologies, and doing so with minimal risks and dangers to individuals and businesses that own the data.
We looked into the data trends from 2016, and analyzed their applicability alongside newer trending technologies poised to make an impact to businesses this 2017.
Top 7. Data Security
A visualization by the World’s Biggest Data Breaches showed that there were only five companies affected by a data breach with losses greater than 30,000 records in 2004 and 2005. From 2010 onwards, there were more than 20 companies affected each year. That was a 300% increase in data breaches, which is defined as “an incident in which sensitive, protected or confidential data has potentially been viewed, stolen or used by an individual unauthorized to do so.”
Ponemon Institute declares in their 2016 Data Breach study that there is a 26% likelihood of a breach in over 24 months. Results from the study show that the average total cost of a breach is $4 million, which is 29% higher than the cost in 2013. The average cost per record is $158, but it ranges for different types of organizations and industries, from $355 for the healthcare sector, to $172 for the retail industry, and $129 for the transportation and logistics domain.
To lessen the percentage of being affected by a data breach, companies must prioritize protecting their data. Data Security refers to protective digital measures to prevent data breaches and data corruption. Examples of data security technologies are data encryption, software/hardware encryption, data masking, data erasure, and backups. Securing data is important not only for corporate proprietary information, but the data of partners, clients, and consumers can also be at risk. Clients now avoid doing business with businesses that cannot safeguard their information.
Top 6. Dark Data
Every day, consumers generate billions of data that organizations collect and utilize to improve their products and services. With that much data, not all of it gets processed. Such excess and unused data is called Dark Data. Gartner describes Dark Data as “information assets that organizations collect, process, and store in the course of their regular business activity, but fail to use for other purposes.”
This type of data may seem dull and insignificant, and organizations tend to consider it useless and simply store it for potential use in the future. Little do some businesses know, Dark Data is important; not only does it contain hidden insights and opportunities, but leaving it in the corner overlooked and unprotected can result to security, legal, and regulatory requirement issues.
Dark Data is a billion dollar opportunity that can help create new revenue opportunities, develop new partnerships, and shift businesses into the data-driven century. Organizations just need to be able to manage and analyze it because there is more to the tip of this iceberg.
Top 5. Digital Twins
Imagine being able to view a working factory from the screen of your device. There is no need to be physically present at the factory since you can view the software model of it that shows issues — e.g. when a machine stops working or when there is a shortage of supplies.
Different objects and processes in this world are slowly becoming digitized; forming a digital twin. Basically, a digital twin is a virtual representation of a product, process or service. Digital Twins make use of software on a cloud-based platform to gather and analyze data that enable businesses to monitor efficiently and react quickly to problems.
For energy companies, the digital twin creates cloud-based computer models of wind farms to determine the best way to operate turbines more efficiently, that is, maximizing energy output while minimizing degradation of the machines.
In the airline industry, the digital twin makes use of reams of data from the sensors on planes to help carriers optimize routes and fuel intake, and minimize unplanned maintenance. This allows planes to profitably stay longer up in the air, while still arriving on schedule.
In healthcare, doctors can monitor patients and be alerted if there are any issues just by looking at the patient’s digital twin. It enables the collection and analysis of information such as the person’s heartbeat, blood pressure, and perspiration.
The expectation is that digital twins will help different industries, businesses, and organizations monitor and react faster and efficiently to problems and issues. They will also be able to experiment with different processes and operations to determine which are more cost- and time- efficient.
Top 4. Robotic Process Automation
Robotic Process Automation (RPA) technology enables software robots to replicate tasks within a process. This frees up human employees to work on more critical tasks that require reason, judgment, and emotional intelligence instead.
According to the Institute for Robotic Process Automation (IRPA), there are several business benefits of RPA:
- A software robot can work 24/7 throughout the year at a lower cost than its human equivalent.
- Using RPA is more efficient because it increases production, reduces cycle times, and decreases the need for ongoing training.
- Robots are consistent, accurate, and can do their tasks without any errors, thus providing better quality and performance.
- Process automation makes use of advanced analytics to achieve regulatory compliance, cost effective growth, and optimized operations.
With RPA, EnableSoft was able to lower costs, increase productivity, and efficiency of CB&S Bank. This American bank recently expanded and needed to move massive amounts of data to their core system. EnableSoft helped implement an RPA software to load and fund lines of credit, as well as for closing and adding addendums. The process usually took two to three hours but was lessened to thirty minutes to an hour with RPA. It also saved 900-employee hours in a year’s time.
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