MONTVALE, N.J., April 12, 2018 — DATA Inc. today announced the launch of nova IQ, a highly specialized business enablement service that will help partners accelerate their entry into the world of new opportunities that is being made possible by the emergence of disruptive technologies, while reducing the cost and risk of enterprise innovation programs.
Read the full official release at DATA Inc. Announces the launch of nova IQ
Finding a suitable job opportunity is as critical as getting through the interview. The task requires a lot of attention to detail, from checking the required skills and experience to location, work hours, compensation and benefits, everything is important.
Here are a few tips to help you identify a great next job opportunity.
Look beyond the Job Title
When looking for a job, many can reject a vacancy by only checking the job title, which may not match their desired job. However, Glassdoor recommends that candidates look at the entire job description and not settle for job title only. For example, a post with title Software Engineer can be very generic, the job description may explain that the requirement is for a specific skill that matches your experience perfectly.
Do not rely only on alerts
Registering with a job portal is simple. It is easy to fall into the trap of relying on them to provide alerts and notifications. However, it is advised to log-in and search for work offerings on the portal. Make sure you do not miss out on new vacancies. Also, if you will widen your search for a role on a portal, and also look at the suggested Vacancies. You may find a matching opportunity.
Good interview preparation
Never fall into the trap of overconfidence, always prepare for an interview well ahead of time. Brush up on your technical skills. Present them in a manner that is of benefit to the client and the role in question. Look for related questions on the online and prepare potential answers.
Tip: Ask a friend to help you do a mock interview.
Make sure that you take the job description with you, the description can be helpful to you at the time of interview. Referring to the description, you can exactly tell the recruiter your capability for the required skills and experience.
Time to become a listener
When you are asked in the interview, if you have any questions, this moment is the best time to demonstrate the interest in the role. Some good examples include, what are their expectations from you, what is a usual day, how do they measure your performance, what are their plans for the future etc.
Engage in conversation
It is not likely that you will be selected immediately after your interview. Therefore a thank you mail for arranging the interview is always a good way to follow up. You could include why you would like to be a part of the company.
Tip: Post or share something on LinkedIn which might grab the interviewer’s interest.
Appraisals and Salary review meetings are not less than a nightmare. Even if you are a gold miner of your company, these meetings haunt you. For the reason, that you will need to do a lot of efforts to prove your worth. Thanks to the organizational culture. However, if you go prepared like a warrior, you will win the battle. Finding growth in your current workplace is easier than hunting for a new one.
Here are few steps to ensure that you get a good salary hike
Timing: While asking for a hike, the most important point to consider is the timing. If the company is doing good with people, making good money, then it’s the right time. Choose the time wisely so that you do not get to hear a “No”.
Tip: Involve in conversation with your boss and seniors to know the progress of the company revenues. We also suggest looking for the mood of your boss.
The way of Asking: Preparing for an appraisal interview is as important as a job interview. The way you will ask for it, consequently decides a lot in the first place. Prepare to clearly establish your expected hike. First, jot down points to explain why you deserve the hike and then prepare for the conversation. Assess your performance prior to the appraisal by gathering all the facts and figures.
Tip: Do a mock interview round with your friend and think of counter questions. Prepare all answers in advance.
Research: We all consider our worth to be high, however, it is important to know some facts and figures. Do a market research before you set up an expectation for yourself. Also, check on Glassdoor for salaries of people working in same experience and job group. Similarly, you can also check the offered salary on the competitor’s job portals.
Tip: Do homework on how market offers to other in the same position. Look at salary surveys, trade magazines and job portals.
“I will Quit”: The most perilous statement in the life of an employee. We as recruiters will strongly suggest you to never threaten with quitting or resigning statements. Certainly, such statements kill the chance of getting good hikes positively. In some cases, your boss may think of giving you hike after this statement, but that will have a bad impact later. Which includes friction in the team and unrealistically high expectations in results.
Tip: Quitting for appraisal will never go in your favour until you have a second option in hand. Manage the conversation to win hike and not lose the job.
Invest in your career: Usually, companies offer training programs for skill upgradation. For example, DATA Inc provides training to our Software Development team and Recruiters. However, if your company is not offering you a training, do it yourself. Upgrade your skills by undergoing some reputed training courses related to your skillset. This will help you prove your enhanced knowledge for a project which requires more skills. Above all, if a company is giving you a good hike, they will expect better results from you.
Tip: In the appraisal, you can also ask the company to pay for your training program as an added benefit. Since you have already done the training and you can demonstrate its benefits, the company should be ready to pay for it.
Furthermore, if your appraisal meeting is coming soon, follow these steps to prepare yourself for the big day. If you do not get the appraisal as you thought, do not get disheartened. Prepare yourself for better challenges and results. If you are planning to switch your job, we must have a role for you. Share your resume at firstname.lastname@example.org or look at open positions with our clients.
Ask someone their take on emerging technologies and it will revolve mostly around Machine Learning, Artificial Intelligence, Internet of Things, Blockchain etc. Certainly, these topics gathered a lot of buzz in last years. However, the technology industry is yet to take up many new innovations. One of them is “Differential Privacy”.
Technology never stops challenging itself. Large-scale data breach received much attention last year and is expected to grow. This year, we share the concept introduced in June 2016, but still not much explored – Differential Privacy. Apple introduced it at their Worldwide Developer Conference held in June 2016. Craig Federighi, senior vice president of software engineering shared at the event, “Differential privacy is a research topic in the areas of statistics and data analytics that uses hashing, subsampling and noise injection to enable crowdsourced learning while keeping the data of individual users completely private. Apple has been doing some super-important work in this area to enable differential privacy to be deployed at scale.”
Statisticians will be at the core of deploying this technology in enterprises. It encrypts personal data without disturbing the program to extract accurate data from a dataset. Simply putting, this technology would secure data from hackers to access personal information from a database. However, it will ensure that big data tools are still able to predict insights.
Apple boasts of not keeping its user’s personal information however the company completely understands the importance of this data in the era of big data analytics and machine learning. To answer this paradox, they came up with this concept of Differential Privacy. Craig also emphasized that Apple does not assemble user’s data. Apple tries technological advancements to keep the data in user’s device than on Apple’s server.
Though it is in nascent stage or we can say this is a concept, Apple is betting big on it.
This statistical science will presumably learn patterns and information about a group of people, refraining from collecting an individual’s data. Differential privacy will collect and store data in a format which extracts insights on human actions. These include their likes, wish-list, patterns, searches etc. But it cannot extract anything about a single individual. Probably we can say, that this technology will group the people with same patterns, likes and actions. It will provide useful insights but will not let attackers get access to a user’s data.
Apple announced to introduce this technology in iOS10, however researchers are debating on its success. They say that Apple has not been completely successful in implying its promise of privacy. Today, Apple is clearly the privacy leader among technology companies. So, it will be interesting to see how the tech giant will successfully implement this novel technology of data science.
Pretext: “Intelligence is the ability to acquire and apply knowledge”. Machines are made intelligent when they are trained to learn patterns using human intelligence through Artificial Intelligence. What if a Machine can train the other Machine?
We have heard about Robots assisting humans in most tasks. Wherein a software engineer trains a machine learning algorithm about patterns and methods so that the robot can perform the task again. Robots store this learned behaviour in a central repository called RoboBrain that’s accessible by other robots. However, with Robots came many technical challenges which are still in the process of transformation.
Today, talking about machine learning is a widespread phenomenon. A significant example of machine learning, which received highlight in 2015, was a driverless car. It is a car which understands the driving patterns of its owner and gets trained over a period. Tesla launched Model S with the vision to provide driverless car assistance to its owners. Surprisingly, after some time the car itself learnt the driving skill and route options. “Each car could improve its own autonomous features by learning from its driver, but more significantly, when one Tesla learnt from its own driver—that knowledge could then be shared with every other Tesla vehicle”. – Tesla CEO Elon Musk.
Navigating through technological transformations, one can determine that the speed at which machine learning software is working, it is going to create maintenance challenges. The systems are improving exponentially.
What comes as more surprising, is the concept of Machines communicating gained knowledge and teaching other Machines. Regardless of the progress, the competition between two machines is the darker side of the development.
The training of data is not an easy deal for machines. The data is the raw material for this practice. However, the data available is unclassified. The variance in the data creates asymmetrical experiences. When the object in question is a machine, the variable data can create an array of misinterpreted information and loss of previously stored information. This situation will impart a significant effect or defect in some cases.
A machine learning knowledge from a central repository located miles away, and performing tasks using the same knowledge, is incredible.
For example, one driverless car may take significant time to learn to navigate a particular city, while one hundred driverless cars can navigate that same city together. Using and sharing the knowledge they learnt, can drastically improve their algorithms in terms of quality and time.
The future of Artificial Intelligence resonates the useful information sharing between machines following common patterns and goals. It will be interesting to see if someday, the same machine algorithm can be used for performing different tasks with different goals. For now, all AI-powered devices continue to leverage this shared knowledge transfer. This enables faster learning, taking the pace of development to another level.
Well, we must consider that today we have only started with these technological advancements, as most of the projects are running in their test phase. We are yet to witness the wonders of technology infused with human skills.