Tools (22)

Can Big Data Help Avert Catastrophes?

Disasters are becoming too complicated and common in the world. Increasingly, rescue and humanitarian organizations face many challenges as they try to avert catastrophes and reduce deaths resulting from them. In 2017 alone, it was reported that more than ten thousand people were killed, and more than 90 million were affected by natural disasters worldwide. These disasters range from hurricanes and landslides to earthquakes and floods. The years that followed turned out to be equally calamitous, with things such as locust invasions, wildfires, and floods causing havoc across the planet.


Who Should Manage Your Hadoop Environment?

Hadoop is the leading open source technology for the management of data. In any discussion about big data and its distributions, you will never fail to come across Hadoop in the middle of the talks. As outlined in a technical paper by Google in 2006, it was designed as a distributed processing framework back in 2006. It was first adopted by Yahoo in the same year, followed by other tech giants such as Facebook, Twitter, and LinkedIn.  During this time, Hadoop evolved significantly into one of the most complex big data infrastructure known today.


What is Important in Data Transformation?

Data has become one of the critical components of any business in the modern era. It is for this reason that you keep hearing some conversations around big data and big data analytics. With this, data transformation has also gained fame. It is the process where data is analyzed, reviewed and converted by data scientists from a given format to another. This process is essential for organizations, especially at a time when data integration is required for an effective running of operations and security. It might involve the conversion of large amounts of data and data types, elimination of duplicate data, enriching data and aggregating it. Here is how data is transformed:


Have You Solved All These Big Data Issues?

Big data is a unique technology both in terms of its size and scale. With the advancement of machine learning and data science, big has a potential of impacting live and operations in different industries, in unprecedented levels and scope. Over the past decade, the amount of data generated by different industries has increased substantially. While more data can create an opportunity for businesses, it can also mean more problems if not well used. Here are some of the big data problems that must be solved to get the most:


Big Data is Critical to the Transportation Industry

Big data is expected to be a force to reckon with in the future in the transport and logistics sector. But the benefits it promises to offer are already being felt. Before going deeper into potential uses of this technology in the future, one has to know areas in which it is being leveraged now. As the demand for transportation and freight services rise, companies are forced to embrace new opportunities, including those provided by big data.


Production Improvement Enabled by Big Data

In the modern data-driven economy, competing successfully and making sound investment decisions is a competitive endeavor that is also costly. It is for this reason that you are likely to hear discussions in professional business circles about big data and big data analytics. In the manufacturing sector, manufacturers look for ways that drive production, enhance efficiency, and increase innovation. This is where big data becomes highly useful. Big data allows companies to achieve productivity, gain efficiency in operations, and uncover new insights that drive innovation. With big data analytics, manufacturing companies can get information and patterns that will enable them to improve their processes, efficiency of supply, and identify aspects that affect production.


New Way to Share Data

According to Tech Crunch, InfoSum has raised $15 million in funding to bring its new way to share data to market.

Data protection and data privacy have gone from niche concerns to mainstream issues in the last several years, thanks to new regulations and a cascade of costly breaches that have laid bare the problems that arise when information and data security are treated haphazardly.. 


How Can Pharmaceuticals Win the Fight Against Cyber Criminals?

Pharmaceutical companies, like much of the healthcare industry, are facing massive cybersecurity challenges, with insider threats costing health and Big Pharma $10.81 million in losses annually. External cyberthreats have proven to be a major concern in the industry as well, even outpacing insider breaches in the past year. Further troubling is the course of action taken by such malicious actors, who rely on insecure email communication as an invitation into an organization’s network.


Changing Social Science Through the Use of Big Data

As accurate as it is, talking about how vast amounts of data can help solve most of the world’s pressing issues has become a cliché. This, however, does not mean that the importance of big data in solving these problems should be overlooked. Big data is helping in solving many problems more efficiently than before. In many industries, data is being leveraged alongside the advances in data science and the tremendous growth in computing power to solve specific problems fast and effectively. In industries where people have been struggling to make meaning out of vast amounts of text data, for example, machine learning can be used to identify patterns hidden in this data that would have otherwise have gone unnoticed.


Protect Your Organization's Data Against Cyber Threats

Cyber attacks are imminent. According to a ThreatPost article, “Most organizations have experienced some type of attack within the course of a year, with only 7 percent of respondents claiming not to have experienced an attack at all.” An organization must change their rationale from “what will we do if we get attacked” to “what will be do when we get attacked.”  Having a solid plan will decrease the time it takes to fend off the attack and save the company thousands of dollars.


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