Big Data Analytics

Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. With today’s technology, it’s possible to analyze your data and get answers from it almost immediately – an effort that’s slower and less efficient with more traditional business intelligence solutions.

So, What exactly is Big Data?

Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy.

Why is Big Data Analytics Important?

Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers. In his report Big Data in Big Companies, IIA Director of Research Tom Davenport interviewed more than 50 businesses to understand how they used big data. He found they got value in the following ways:

Cost reduction

Big data technologies such as cloud-based analytics bring significant cost advantages when it comes to storing large amounts of data – plus they can identify more efficient ways of doing business.

Faster, better decision making

With the speed of in-memory analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately – and make decisions based on what they’ve learned.

New products and services

With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want. Davenport points out that with big data analytics, more companies are creating new products to meet customers’ needs.

What Challenges does it face?

Potential pitfalls that can trip up organizations on big data analytics initiatives include a lack of internal analytics skills and the high cost of hiring experienced data scientists and data engineers to fill the gaps.

The amount of data that's typically involved, and its variety, can cause data management issues in areas including data quality, consistency and governance; also, data silos can result from the use of different platforms and data stores in a big data architecture. In addition, integrating Hadoop, Spark and other big data tools into a cohesive architecture that meets an organization's big data analytics needs is a challenging proposition for many IT and analytics teams, which have to identify the right mix of technologies and then put the pieces together.

Autonomous Vehicles: Future Of Personal Transportation

What’s the future of personal transportation? Well, you’ll likely be spending a lot less time behind the wheel, for one. The rise of self-driving cars means that some scenes out of science-fiction flicks (think Total Recall or I, Robot) are now reality—and even more will be available soon

So what exactly are these autonomous vehicles?

An autonomous car (also known as a driver-less car, self-driving car, robotic car) and unmanned ground vehicle is a vehicle that is capable of sensing its environment and navigating without human input.

Cars today already include many semi-autonomous features, like assisted parking and self-braking systems. And completely autonomous vehicles—able to operate without human control—are rapidly becoming more of a reality. You’re probably familiar with Google’s version, which has made headlines with its Google Chauffeur software, which the company hopes to bring to market by 2020.

Why do we need them?

The pros of autonomous cars are many. “The sensors in a self-driving car are always observing, are not affected by the state of the driver (sleepy, angry, etc.), and can scan in multiple directions simultaneously,” says Dr. Dominique Freckmann, an automotive engineering manager at TE Connectivity, a global technology leader providing connectivity and sensor solutions that are essential in today’s increasingly connected world. “Autonomous driving is a key aspect of the industry’s drive toward safer roadways.”

“Recent NHTSA research shows that approximately 94 percent of accidents are caused by human error,” adds Alan Amici, a vice president of automotive engineering at TE. “Cars with advance safety features and eventually, self-driving cars, can significantly reduce the number of collisions. The impact of this innovation can be far-reaching, including reduced demand on emergency response systems and reduced auto insurance and health care costs.”

What technology makes self-driving cars possible? 

It’s really three technologies: sensors, connectivity, and software/control algorithms.

“Most of the sensors required for autonomous driving are available today and are used in advanced safety features such as blind-spot monitoring, lane-keep assistance, and forward collision warning,” he says. “Sensors for other features such as radar, ultrasonics, and cameras provide the input necessary to navigate the car safely.”

Connectivity means cars have access to the latest traffic, weather, surface conditions, construction, maps, adjacent cars, and road infrastructure, he says. This data is used to monitor a car’s surrounding operating environment to anticipate braking or avoid hazardous conditions.

Finally, software/control algorithms are needed to reliably capture the data from sensors and connectivity and make decisions on steering, braking, speed, and route guidance.  “By far the most complex part of self-driving cars, the decision-making of the algorithms, must be able to handle a multitude of simple and complex driving situations flawlessly,” Amici says. “The software used to implement these algorithms must be robust and fault-tolerant.”

With so many advantages, why don't we see these cars more often on streets?

While technologies and capabilities continue to evolve toward making autonomous vehicles a reality, there are some hurdles. Right now, autonomous cars are legal only in a few U.S. states, as regulators weigh how to best ensure their safe interaction with standard human-driven vehicles.

“Self-driving capability will add benefits to our whole society, such as providing transportation for people who are otherwise not able to drive because of age or physical impairment,” Freckmann says. “That is both exciting and meaningful.”

Soon, your car will be able to drive itself faster and safer, while you relax in the seat.