Happy New Year from us at ExactData! With each new year the aspiration to evolve technology even further grows exponentially, and the once thought to be improbable becomes possible right before our very eyes through both sustainable and disruptive innovations.
2020 promises to bring massive changes to the tech world, which includes but isn't limited to:
The terms "database" and "database management system" are typically used interchangeably despite the fact the two mean completely separate things. Additionally, both are important terms that those in the technology industry should clearly know how to distinct between, but it seems many people either don't or can't. Very quickly, below are definitions for the two vocabulary terms.
A database is a logically modeled cluster of information [data] that is typically stored on a computer or other type of hardware that is easily accessible in various ways.
A database management system is a computer program or other piece of software that allows one to access, interact with, and manipulate a database.
Additionally, there are many types of database management systems that exist in the world today. Historically, relational database management systems (RDBMS) are the most popular approach for managing data due to their accessibility and performance result capabilities. Examples of RDBMS's include the Amazon RDS, Oracle, and MySQL which all utilize Structured Query Language (SQL) to manipulate the different databases they interact with. All RDBMS's are ACID compliant and typically implement an OLTP system.
To combat the limitations of relational database management systems, NoSQL databases became more popular over the years. The term "NoSQL" was coined by Carlo Strozzi in 1998 as the term for his first database which didn't utilize SQL for managing data, hence the label "NoSQL." Examples of popular NoSQL databases include key-value pair databases, document databases, graph databases, and columnar databases, all of which while are similar in concept are different in theory, as there are advantages and disadvantages to using each in different scenarios.
As we continue to move forward in the technology world, we constantly search for the most optimal solution for all of our data needs. These optimal solutions begin with which database management system or systems we choose to utilize to solve our data-related problems. Some database management systems are more equipped for certain scenarios than others, and figuring out which type works best for you is essential when working with big data.
Most scientists agree that no one really knows how the most advanced algorithms do what they do, nor how well they are doing it. That could be a problem. Advances in synthetic data generation technologies can help. These algorithms generate data with a known ground truth, sufficient volumes and with statistically relevant true and false positives (TP, FP) and true and false negatives (TN, FN) for the nature of the test. AI algorithms can now be measured for precision, c, as the fraction of the predicted matches that are true positive matches, or c = TP/(TP + FP).
Coming soon to our website is our sample data page where users will be able to request and access some of our sample data to get a better feel of what we can do! We'll have different types of sample data available such as sample tax data, follow the money data, sample cyber security synthetic log files and more!
On Thursday, November 7th the Institute for Robotic Process Information & Artificial Intelligence (IRPA AI) New York Chapter Launch Party will be taking place in Manhattan, New York on 25 West 39th Street on Floor 14. The launch party will include a pre-launch networking event for the new chapter beginning at 5:15pm which will serve as an opportunity to plan and discuss future programs for the chapter. The launch party will also inform guests on how they can be involved with the chapter. Drinks will be served at the launch party during the pre-launch networking happy hour!
For more information or to RSVP to the event, please follow the link here.
For questions or general inquiries about IRPA AI or the NY Chapter Launch Party, please contact Molly Alexander at Molly.Alexander@irpanetwork.com.
You can also learn more about IRPA AI by going to their website and or their LinkedIn!
In recent news, Pitney Bowes and Groupe M6 experienced ransomware attacks which limited customer access to company services and led to the encryption of information on private networks and systems belonging to the companies. Furthermore, email servers and phone lines also went down due to the attacks, and while no customer data was lost or stolen, shows how much of a threat these ransomware attacks can pose on the privacy of companies and their customers.
Ransomware attacks, while hard to detect and fight off, are able to be defeated with time and effort. However, if it takes too much time to defeat said attacks, valuable data could be breached or stolen and many will be put at risk. If the risk is too much, companies forego hopes of fighting off the attacks themselves and end up paying high extortion fees to minimize damage. However what happens when attackers strike again? Will the companies be prepared to fend it off the next time, or will be they be seen as an easy target because they gave in?
One thing is for sure; just as we continue to make strides in the cyber security industry, criminals continue to get more and more advanced with their own cyber attack tactics.
The TAG Cyber Security Annual has been released on their website! You can find it here!
The TAG Cyber Security Annual comes complete with unbiased, expert industry research so we recommend the read! Alternatively, you can download the Annual here!
With the recent Equifax breach coming back into the limelight due to the cancellation of the $125 check the FTC promised to those impacted by the breach, we want to take a look at possible prevention for the breach in the first place, or at least ways that the damage could have been minimized.