SigmaWay Blog

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

E-Commerce firms very well understand that data is a wealth. The data can provide very crucial and meaningful insights, if used properly. Data Mining is one such way. It is a field of computer science that discovers the patterns in large data sets. This is done using the methods of Artificial Intelligence, Machine Learning, Statistics and Database Systems. Algorithms are made to act on the data set. This often reveals "game changing" results for the industry. Data Mining can be either done manually or can be automated. E-Commerce Firms use this to get to know more about customer's emotions, preferences, and other factors that impact their purchasing style. So they excel in offering a personalized experience through this. It doesn't stay limited to customers. Data Mining is done to keep an eye on the competitors. Read more about it in the article written by Arie Shpanya (contributor to Econsultancy)  at: https://econsultancy.com/blog/67360-why-data-mining-is-the-future-of-online-retailing/

Before we start discussing about Tools for Social Media Analysis, first of all we have to know what social media analytics is? Instead of thinking it as a noun, take it as a verb. Precisely, it's gathering data from social platforms to help guide marketing strategy.

# the process begins with the prioritizing goals.

# The second step is determining key performance indicators (KPIs) i.e. likes and shares your posts receives, replies and comments, and more importantly the clicks your links and content earn analysis.

Now, as the definition is clear, we will directly come to the social media analytic tools. To read more, follow: https://keyhole.co/blog/list-of-the-top-25-social-media-analytics-tools/

Finding suitable talent for your workplace is a difficult process. It is much more difficult to retain talent, if the workplace conditions are not suitable. Most of the organizations use annual feedback system to know about the employees. But the better way is to have a continuous check on the performance and behavior of employees. This helps in getting a better picture. Big Data helps in identifying the relation between engagement and retention. Cloud based solutions provide access to all the data at one place and this can be used for further decisions by HR. Data can be collected, measured, analysed at one place. And accordingly solutions can be thought of to eliminate the problem. Organizations who use big data solutions have observed a better turnover. Read more at: http://www.cio.com/article/3023311/careers-staffing/how-big-data-can-drive-employee-engagement.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

Firms often spend a huge amount of money on display marketing. But as a consumer, do you remember at all the last display ad you saw. The answer is NO. Display Marketing can be very effective if targeted. It is important to know which item should be placed on which site and what part of the site. Most vendors don't go into details of the strategy, thus shelling out more money out of those interested in display marketing. Algorithmic attributions can be used to determine how the impressions will impact the ROI. Learn more about it in the article written by Sandy Martin (Sr. Business Consultant) at : http://blogs.adobe.com/digitalmarketing/analytics/how-to-get-more-from-display-marketing-with-analytics/

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/

Predictive models are used to predict future outcomes on the basis of data collected from past. Many organizations take their crucial decisions based on the foundations laid by the predictive models. But what if the model goes wrong? "BOOM"- crash of a significant part of the strategy! Though each predictive model has some scope of error. There are chances that the input variables considered for the model were not appropriate. But we need to find out what kind of error and to what extent it is acceptable. There is a need to work on the foundation of the predictive models to prevent failures.  Read more about it in the article written by John Bates(Senior Product Manager for Data Science & Predictive Marketing Solutions) at: http://blogs.adobe.com/digitalmarketing/analytics/what-to-do-when-your-predictive-marketing-is-wrong/

When we talk about Artificial intelligence, we always come across the question,' will there ever be possible that machine replaces humans and preforming better than us?' The answer is partially 'yes', as at least in many things machines are performing as unchallenged champions of creativity and intelligence. Areas where artificial intelligence already performing better than humans are.

• Search the web quicker. Machine learning AI helps in web engine optimization through understanding the meaning of words and phrases, and can therefore guess what should be in the page ranking in never seen before searches.
• Work in deadly environments. Robots can survive in conditions where humans can’t like deep space, the oceans penthouse, or inside a radioactive reactor.
• Get a PhD quickly. Few critics of AI argue that machines could never be creative, or curious, or discover anything of significance, but team at Tufts have proved the naysayers wrong.
• Deliver a correct medical diagnosis.
• Translate in many languages.

Read more at: http://www.huffingtonpost.com/george-zarkadakis/5-things-ai-can-do-better_b_8906570.html?utm_hp_ref=technology&ir=Technology

Why to go far? If we see in our recent past artificial intelligence and machine learning were very exciting and dream topics among engineers and developers. But now machine learning has emerged as the ideal branch of big data and working as oxygen to concepts like artificial intelligence. Year 2015, was a year of massive market shifts. Machine learning (ML) and its super set artificial intelligence (AI) where computer receives new information and learn without supervision have played very important and revolutionary role for the shift. Still Machine Learning has much more in the store. Year 2016 is going be a big year for machine learning. Usually, computers have been used to enhance the ability to carry out tasks. Users see this with features like auto completion and spell check. In the upcoming year these leaps are likely to be made on three fronts: natural language processing, personalization, and security.  To know more about machine learning follow the article written by Motti Nisani(author) at: - http://www.geektime.com/2015/12/27/2015s-big-leap-into-machine-learning/

Those using Predictive Analytics easily outpace those who don't. There is a clear incremental sales lift in the marketing campaigns which consider predictive analytics. Every organization strives to achieve a higher return on investment (ROI) from that spend on marketing. Predictive analytics help creation of unique customer profiles by analyzing the data.  Read more about how Predictive Analytics can be useful in B2B marketing in the article written by Laura at: http://blogs.forrester.com/laura_ramos/15-07-02-the_power_to_predict_can_give_b2b_marketers_an_unfair_advantage

Cloud was an unknown term to almost all small and medium businesses (SMB) 4 years back but now nearly half of the SMBs have adopted cloud. There are many factors behind it. The first is ability to access to data stored on cloud with mobile devices and mobility is very important in today’s world. Second factor is backup and recovery adequacy of cloud which is a cheaper option than buying and maintaining a backup system. Another reason why cloud is an attractive option is that standardization leads to improved data security. With cloud gaining immense popularity in the future any SMB not using it would be a rare site similar to a person not using smart phone in current era! Read more at: http://www.business2community.com/cloud-computing/rise-cloud-small-medium-business-market-01418782#ORT38DDsW5VFwVHp.97

Security is an important aspect in any organization. In case of a security breach, company suffers a loss of trust in addition to money. For security, organizations are storing terabytes of data and with big data analytics security has become a nimble and deterrent strategy. It rapidly spots a suspicious pattern. In enterprise security, a small anomaly can be of great importance. Security breach occurs via an unimportant channel in a long period of time. If the organization has right tools, then only it can detect a hacker’s actions in time. With big data analytics data at rest and real time activity can be monitored with ease and organizations can be safeguarded in better way. Read more at: http://www.forbes.com/sites/centurylink/2015/11/23/improving-data-security-through-big-data-analytics-2/

Even at the time of hiring, workforce analysis influences from starting i.e. creation of a job description and worker roles, till the recruitment of the person with better chances to succeed in the organization. Through the analysis, companies can make better hiring choices and monitoring the performance in real time. This will help companies to refine their organizational structure and develop talent and leadership within the organization. Workforce analysis will also help in reducing legal claims issues. These all will contribute in cost reduction and smooth working of the organization. Read more at: http://www.smartdatacollective.com/sarah-smith/358073/control-business-costs-workforce-analytics

Clickstream is recording of the parts of the screen of a computer user clicks on while web browsing or using another software application. Clickstream Analysis refers to collecting, analyzing, and reporting the data about visitors visit. This is generated by recording the succession of clicks each visitor makes. This helps you to get insights of the behaviour of the visitors. Hence, you can manouver your strategies as per this analysis. It gives you the information of how long a visitor stayed on your website and how often he returns.  This gives a wealth of information to be analyzed.  To know more about clickstream data analysis go through the article written by Jaoa  Correia at: http://www.blastam.com/blog/index.php/2015/04/move-into-limitless-world-of-clickstream-data-analysis

As the field of Data Science is growing, the confusion regarding the skills needed to be a data scientist is also increasing. Most of us think data science skills range from computer science and statistics, to machine learning and strong communication. But, the top data science skills list includes data analysis at the top, followed by others like R, Python and machine learning. As per recruiter lists, R, Python, SQL, SAS and Hadoop are appreciated. To know more about data science skills, follow the article written by Daniel Levine (Content Marketer for RJMetrics) at: http://www.smartdatacollective.com/daniellevine/366486/top-20-data-science-skills

We all have bid our goodbyes to 2015, and as we begin to focus on 2016, there are many accelerating business intelligence trends that must be kept in mind. Business Intelligence continues to be one of the fastest developing areas in 2016. The craving for more advanced and affordable business intelligence tools and techniques is increasing each day. More and more people have begun to realize the world of data and are using it to get some meaningful insights. Read more about top business intelligence trends of 2016 at:http://bigdataanalyticsnews.com/10-business-intelligence-trends-for-2016/

Datafication is a process that captures almost every aspect of the world as data. With datafication, interactions can be quantified easily with the help of big data analytics. Data is generated for almost everything ranging from temperature readings to social media. This data is useful for analyzing patterns and making predictions about the future. These predictions not only improve business efficiency and finances, but also boosts customer experience and improve relations with the customer. Big data's tools' ability to extricate insights from the collected data have led to a new information revolution of sorts. Universal applicability is another exciting opportunity in this field. The future of retail commerce seems brighter now as datafication is here to stay. Read more at:http://insights.mastercard.com/2015/07/06/datafication-the-new-buzzword-for-business/

This New Year, let's look back at the marketing experiences throughout 2015. We have learned that the fundamental concept of digital marketing is unaltered, no matter which industry we target. But, it teaches us to adapt to changing habits and practices of customers. Here are 3 digital marketing truths you should keep in mind - 1) to grow our presence across different channels, mobile is the only channel that has grown so rapidly. 2) Removing barriers across different channels so that your customer is able to communicate better. According to customers different preferences it's necessary to use data management platforms for organizing information. 3) Use of automation to use right content at the right time. Read more at: http://www.business2community.com/digital-marketing/top-3-digital-marketing-truths-take-away-2015-01413555#Cll3tXd2oAKuqhgF.97

Primary activities of any oil and gas company generate large amount of data. This is developing heightened demand for big data and services in this sector. The market ofr such solutions is expected to grow by $3.99billion to $5.41billion in 2020.  Big data analytics could help in reducing time lag, and improving drilling parameters in identifying any traces in seismic signatures derived from geological and operational data. Employing data analytics can also help detect any abnormalities in drilling and could save millions in labor and equipment costs. Recovery and production can be enhanced by applied analytics seismic and drilling data. One of the major challenges faced by large companies is lack of skilled labor which can be solved with knowledge management using big data. Recent Paris Agreement has created unprecedented opportunity for countries for decreasing temperature less than two degrees celcius above pre-industrial time which encourages oil companies to improve operational performance and efficiency. Read more at: http://www.technavio.com/blog/how-oil-and-gas-using-big-data-better-operations