SigmaWay Blog

There is a big gap between what attackers do and what preventions defenders do to prevent it. The general idea is to build bigger and better blacklists for all the threats known or calculated using better threat intelligence.  We always hunt for easy ways, trying to seek out automation of security infrastructure. But these won't' suffice. The reason is because all the defenses are static and accessible to all. All it takes a hacker is to write a script to bypass these security measures. So a possible solution might be RITA, which stands for Real Intelligence Threat Analysis. Its SANS's free new framework that will help in hunting attackers by extending the traditional signature analysis. Read more at: http://www.darkreading.com/vulnerabilities---threats/introducing-rita-for-real-intelligence-threat-analysis/a/d-id/1323244

The evolution of Machine Learning (ML) is affected by the approach of the tech giants towards it. Open Source Platforms and the data sources also have an important impact on the ML models. Tech giants have realized the importance of ML, and this is becoming the new normal for them. They are now focusing on providing ML models as a Service. These are built for the common usage, not just for the data scientists. Most of the softwares being used for ML are open sources, thus affecting the market of other softwares making sources. Tools like Apache Spark are going to dominate the market. Read more about it on: http://www.infoworld.com/article/3017251/data-science/what-machine-learning-will-gain-in-2016.html

Machine Learning (ML) will have a big impact on economics as it helps in taking properly calculated decisions. The ML methods can be modified to make them fit for using in econometrics. These reduce the risk to failure. Data is the key to success for this. Based on the previous records, a model can be trained. Economists are being increasingly interested in technology. ML can help in clarifying the real situation from what is being assumed. Many technical firms are hiring economists. The mix of proper proportion of technology with the knowledge of economists will definitely lead to great results. Read more at: http://www.forbes.com/sites/quora/2016/01/27/what-will-the-impact-of-machine-learning-be-on-economics/#5bccf597ad5e

In the Healthcare industry, what we really need? Better healthcare results to improve our lives. Healthcare industry generally takes decision using data- like case histories. Well the good news is, now we have lots and lots of data. This is the era of big data, where millions of bytes of data are generated every second. And the bad news is we can't keep up with this fast rate of generation of data. Big data is unstructured which makes it difficult to hunt down relevant helpful information. Using data science with health care we can predict epidemics, advance cures and can provide better, safer and more pleasant experience for patients. Read full article here - http://www.cio.com/article/3001216/analytics/4-big-reasons-why-healthcare-needs-data-science.html

No, remote access should not mean less control. It admins need to examine the problem as quickly as possible but conflicting to user expectations, it's not possible always. Remote access tools are the solution to these problems. Tools like GoToMyPC, LogMeIn, TeamViewer are the quite popular which provides remote access, control and support. But apart from this, remote IT administration is also needed i.e., capability to diagnose the system even before connecting to the server. Microsoft provides such ‘manual’ remote control tools. Goverlan is also one such tool which provides remote troubleshooting. Read more here: http://www.infoworld.com/article/3021938/systems-management/it-admins-remote-doesnt-have-to-mean-less-control.html

A lot is investment is made in the digital marketing campaign. Before planning the campaigns, it is important to correctly determine whether to use Rule Based or Algorithmic Attribution. First, we have to analyze the data in hand properly. If the data is coming from different platforms and needs to be combined or analyzed at one platform, then Rule Based Attribution can't be even thought of, go for the latter. Rule Based Attribution uses the last touch as the final touch, so sometimes it can be misleading. If the journey to the destination has been maneuvered by the smart moves at each step, then we can't rely on the Rule- Based approach. But if the algorithmic approach was that easy, everyone could have adopted it. Read more about the pros and cons of each in the article written by Matt Scharf (Senior Manager at Display Media Operations & Analytics at Adobe Systems) at: http://blogs.adobe.com/digitalmarketing/analytics/rules-based-vs-algorithmic-attribution/

Cloud is the new buzz word. Nowadays, more and more people are willing to shift to the cloud. There are too many paths available for this journey and each path which does appear to be good, might not result in a successful decision. So people need to consider more details than they actually thought. The first step is to categorize types of workload that one wishes to migrate. These are not the applications, but the patterns of processing the applications. Some of the patterns may be - Database-intensive; Compute intensive or; User interface- intensive. If you have, say 200 applications, then, place each application in one of these categories and you will end up dealing with 3 categories rather than 200 applications. Doing so, you will be able to select proper cloud configuration to service your applications. This approach will help you in saving time and money. Read more at: http://www.infoworld.com/article/3016559/cloud-computing/the-right-way-to-migrate-to-the-cloud.html

The fast growing field of "wearables" has brought in one amazing technology. This is being called as "disappearables". The logic behind this is to make technology modest. The wearables should capture energy from the surroundings, sense and observe the environment around. But the challenge for the wearables manufacturing companies is to produce cost efficient products. These should not be restricting the body movements or shall not have the consistent charging issues. This new technology is called disappearables because the user itself can't tell whether he is wearing the smart wear or not. Read more about this amazing technology in the article written by Ben O'Brien (Contributor) at: http://www.entrepreneur.com/article/254301

Hadoop and Apache Spark are seen as the competitors in the world of big data, but now the growing consensus is that they are better convention in together. Here is a brief look at what they do and how they are compared.  1. They do different things: Both are the big-data frameworks, but they do not serve the same purposes. Hadoop is a distributed data infrastructure. It also Indexes and keep track of that data, enabling big-data processing and analytics. On the other hand, Spark is a data processing tool. Secondly, both can be used individually, without the other. 3. Spark is faster 4. You may not need Spark's speed: Spark is fit for real-time marketing campaigns, online product recommendations, cybersecurity analytics and machine log monitoring. 5. Failure recovery: differently, but still good. Read more at: http://www.computerworld.com/article/3014516/big-data/5-things-to-know-about-hadoop-v-apache-spark.html

There is a prediction that by 2017, 33% of Fortune 100 companies will experience information crises due to lack of adequate testing measures. To prevent this, the robust testing approach must be used. Developing a well-planned data warehousing, testing process will help in minimizing such risks. And while moving to agile, we can do more testing in comparison to traditional projects. The testing being done during development in parallel aids to agile development, because development and testing can be completed in a single sprint. The roadmap for building agile data warehouse will consist of following steps-

·         Build business conceptual model

·         Grass roots Data governance

·         High-level architecture with repeatable design patterns

·         Strong testing tools

·         Robust data quality program

·          Self-managing teams.

Read the full article here http://www.cio.com/article/3012097/data-warehousing/take-testing-seriously.html

It's no more difficult to shop at a new place with Location Based Marketing. We often look for the unique and best products, when we visit a new place. A common practice is to inquire about the best deals, with the people around who are aware of the new place. But with everything becoming techy we have Location Based Marketing to rescue. It integrates mobile marketing with location based services. The motive behind this is to make mobile users aware of your presence, while they are in the areas nearby. Most relevant display ads as per user's location are sent. Their interest can be pulled by either providing some discounts or some other perks. This benefit both the user as well as the business. Read more about it in an article written by Jack Simpson (a Writer at Econsultancy) at: https://econsultancy.com/blog/67418-what-is-location-based-advertising-why-is-it-the-next-big-thing/

We all have heard Time is money. Speed is one of the most important factors which determines cost in IT industry. So here are the five actions which will increase speed and productivity and will result in great potential success.

1. Integrated service play.

2. Establish a new strategic intent driven by business rather than function.

3. Reorganize the computer structure by making cross functional teams that work across different disciplines.

4. Invest in the appropriate and technologies.

5. Consider options for renting with technologies like cloud. Read the full article here: http://www.cio.com/article/3022757/it-strategy/5-moves-to-make-your-it-group-more-responsive-to-business-demands.html

We've been thinking about the Internet of Things all wrong. According to various predictions by various companies, there were various statements specifying volume and amount of money, number of connections. These are just numbers, Numbers, more numbers. If we believe in the predictions, there is no way that current analytical solutions can manage that level of information. In the immediate future artificial intelligence capabilities are required. Which means all companies who have an analytics platform play will have to invest in A.I. research, acquire and finally emerge with solutions based on methods beyond machine learning. Or risk being left behind. If this sounds vaguely familiar, it's because right now all efforts are pointing towards machine learning and algorithms as the goal for analytics. To read more visit on: http://www.forbes.com/sites/theopriestley/2015/12/08/a-series-of-unfortunate-tech-predictions-artificial-intelligence-and-iot-are-inseparable/#39f25ec8523a1253d985523a

The trend of wearables is growing hotter each day. BYOD (Bring Your Own Devices) and IoT (Internet of Things) clubbed together, is adding more efficiency and flexibility. It's no surprise that smart wearables are already passé for fashionistas. On the counterpart, these trends are attracting the attention of hackers. Wearables are being profoundly used for both business and personal purposes. Thus making them a rich source of information. This could act to the disadvantage if the information gets into the wrong hands. Though the wearables have not revealed any big disadvantages, so far. But as always, with evolving technologies, there always exist weak points. The hackers find these weaknesses and exploit it to their benefit. So it is essential to do proper research on the wearable, before handling it a prominent portion of your information. Read more about it in an article written by Jen A. Miller (a freelance journalist) at: http://www.cio.com/article/3022059/wearable-technology/how-secure-are-wearables-anyway.html

In today's world Data Scientist is the most- desired workers in IT industries. Since the demand for such skills is high, this has become a desired job for the potential candidates as well. So here are some skills which will increase your chances of hiring, if you want to become a Data scientist - SQL, Hadoop, Python, Java, and R. Not only these, but MapReduce, Hive and Pig skills which will increase your desirability as a data scientist. So, gear yourself up and start working and learning these skills to become a data scientist. Read more at: https://adtmag.com/articles/2016/01/08/data-science-skills.aspx

The Internet of Things (IoT) is impacting on consumers’ lives and corporate business models. It is increasing at the rapid rate and by 2020, more than half of the major new process will incorporate some element of the IoT. IoT is basically connecting device with an on and off switch to the internet. By 2020, a black market exceeding $5 billion would exist to sell fake sensor and video data for enabling criminal activity and protecting personal privacy. To address this compromises in IoT security will have increased security costs to 20% of annual security budgets. To read more visit on:  http://tech.firstpost.com/news-analysis/by-2020-more-than-half-of-new-business-processes-will-incorporate-some-element-of-iot-says-gartner-295467.html

We all are aware of the revolution brought by the cloud computing in today's business functionality. The management and storage of big data in cloud is well known to everyone. One of the best outcomes of cloud based solutions is the Hosted VoIP technology which is changing the way we communicate. On an average, 7 out of 10 telecom customers still do not understand what Hosted VoIP is. In short, VoIP is the concept of using the internet and cloud based servers to place calls instead of using traditional PBX boxes and phone cables. The same concept applies to telecoms solutions built on a larger scale. Irrespective of the type of business Hosted VoIP is beneficial to all. To read more about Hosted VoIP visit at:http://www.smartdatacollective.com/josh-rose/367715/72-people-aren-t-familiar-hosted-voip

A system outage is worse than a nightmare for the IT managers. Downtime is when, the system on which your business relies is dead, down or unavailable. In spite of any levels of preparation, this problem is faced by most of the organizations. And the recovery period builds astronomical pressure on the IT team. A report suggests that the majority of the system outages is due to ill planning. System Outages lead to huge revenue losses each year. Downtime affects the reputation of the business firms significantly. Read more about system outage at: http://www.evolven.com/blog/downtime-outages-and-failures-understanding-their-true-costs.html

Cybersecurity is a very important and is becoming one of the biggest worries for companies. According to various surveys, companies are investing a lot of money in cyber security and training their employees in it. It is estimated that till 2020 investment in the cybersecurity will be around $170 billion. In today’s world as the data is rising, so the risks on it are also increasing. The pattern classification systems that machine-learning algorithm rely on themselves exhibit vulnerabilities that can be exploited by hackers. As we know machine learning algorithms train themselves with the training data set so it may be manipulated according to the needs as hacker wants. For example, Search-engine-optimization algorithm was trained and manipulate website content to boost results in the search ranking or senders of junk emails try to fool spam-filtering algorithm. Even the results of the public election can also be affected by 20% or more as it is found that the order in which candidates appear in search results can have significant impact on perception. To read more about Cybersecurity risks, follow the article by Dr. Kira Radinsky (CTO and Co-founder of SalesPredict) at: http://blog.kiraradinsky.com/author/kiraradinsky/