SigmaWay Blog

Retailers need to connect, track and collect data from assets and customer shopping patterns. Business intelligence tools have become must-have resources. Now firms became more proficient in modern analytics management, including the front-end requirements for data preparation. The retail industry has not incorporated analytics on a large-scale, and many of the entities have deployed the technology are still in the early stages of use. The starting point for retailers is market basket analysis, which is heavily dependent on third-party data. Retailers are also reported-dependent than other industries. By first getting data preparation and initial archival-related strategies right, retailers can better position themselves for long-term success with their analytics investments. For more read the article written by Jon Pilkington (Chief Product Officer, Datawatch Corp.) at :

http://risnews.edgl.com/retail-news/Retail%E2%80%99s-Latest-Ventures-are-Rooted-in-Analytics104638

Social media platforms are influential sources which are employed by government, corporate, and academics to study human society. Social media has played an important part in getting us closer to the "real" during a conflict. It can also take us further away by constantly viewing conflicts on a buzz feed list or Instagram post which seems to be unreal. To know more, please read the article by Ellie Mae O’Hagan : http://gulfnews.com/opinion/thinkers/does-social-media-really-bring-us-closer-to-the-reality-of-conflict-1.1303773 

Technology is redesigning the automobile industry, giving car manufacturers the best chance to continue to increase sales and keep development cost down. With internet -connected cars, self-driving cars and car sharing apps, here are the most anticipated themes and vehicles at Geneva Auto Show 2016 -:

1. Smaller and Smaller

 Manufactures have found that customers are preferring sub 4 meter, vehicle over sedan cars and large suvs. Though car makers are producing crossover producing 380-430 bhp. Augmented technology is helping manufacturers a lot.

2. Futuristic technology

Automobile Industry is on the verge of wide-ranging transformation powered by the internet, information technology and changing attitudes toward the automobile. Developers are coming up with new technologies, by which people can reserve cars using an app and then use their phones to unlock and drive the vehicle.

3. Efficient Luxury

Manufactures are producing sedan as a plug-in hybrid combining efficient technology with high power as a selling point.

To know more, please read the article by CNN IBN -: http://www.ibnlive.com/news/auto/small-suvs-hybrid-vehicles-internet-powered-auto-technology-and-more-heres-what-to-expect-from-geneva-motor-show-2016-1209435.html

Analytics help retailers move to a unified commerce experience and allow for more targeted, cost-effective marketing. Advanced analytics is used for the optimization of merchandise planning. Real-time analytics is integrated with customer and product information across all channels. Retailers have the ability to use science and algorithms to optimize pricing strategies to reduce markdowns, improve demand forecasting to optimize inventory, localize assortments and optimize space planning. Advances in software and the occurrence of cloud-based solutions enable retailers to think about accelerating their upgrade/replacement cycles. It will help limit overstocking and discounting. With real-time analytics, retailers can market to consumers on a 1:1 basis based on customer context. Retailers have the ability to know what customers have in their closet, purchase behavior and preferences. For more, read the article written by Forrest Cardamenis : 

http://www.luxurydaily.com/analytics-offer-solutions-to-merchandising-and-marketing-problems-brp/

Customer service is the most effective part of any company. It not only helps to improve customer retention rate, but also helps to understand new market trends. Big data analytics and business intelligence play a crucial role here. Simple web crawling into a social site helps to understand the on-going sentiment and current market trend. Different social responses, video hits, ads and newsletters help to optimize the search results. In other word this process facilitates smother recommendation system and customer centred predictive modelling. To make a better prediction we can use –

1. Connectors help to integrate diverse data sets in different formats

2. Lightweight search facilitates even non-technical data analysis

3. Queries optimizes the search dynamics

4. Enterprise search also scores with its semantic search, which means that the context is recognized and included in the analysis and structuring of the data.

Using all these parameters business enterprises can design a better profitability model.

To read, follow: http://www.computerweekly.com/blogs/Data-Matters/2016/02/search-driven-business-intelligence-intelligence-for-a-customer-centric-business-world.html

We are moving towards a future in which technology will change journalism. Over the last couple decades, media sales and marketing have been on a journal to find effective ways to monetize digital media. Technology engaged journalists in the preparation of visual or audio material intended for dissemination through public media. It includes genres such as news, reports, analysis about a variety of topics including communication technologies, social media, internet, scientific research, robotics and policy regarding the digital world.
To know more, please read the article by Tom Regan(Blogger foe NPR): http://niemanreports.org/articles/technology-is-changing-journalism/

Indian Railways has solved many issues of distressed passengers using social media platforms. Railway Minister Suresh Prabhu said in his rail budget speech that his ministry had set up a social media cell responsible for taking action on passengers' request for help. After turning social media for feedback and complaint redressal mechanism, Railways are helping their passengers more efficiently. To know more, please read the article of Hindustan times -: http://www.hindustantimes.com/india/how-railways-is-acing-social-media-to-help-passengers-in-distress/story-O0mWmcHVSh8iyxatmeMMZK.html 

According to a report, analytics and big data are going to see most vigorous hiring. Established firms and startups are offering handsome income to talented data scientists. Analytics and big data sector have been on consistent growth over last five years and are expected to increase at a compound annual growth rate of (CAGR) of 33.2% and 26.4 % respectively. The demand for data professionals has increased. It has been predicted that in coming times data science is going to have most exciting jobs. Read the full article here: http://economictimes.indiatimes.com/jobs/analytics-big-data-to-see-robust-hiring-high-pay-packets-report/articleshow/51105814.cms

Google, Amazon, and Apple all are tech giants. But apart from being this, they also have one more thing common and that is they all have their data center in rural areas. But this is more of an exception than a rule. Most data centers are located in or close to a city. These giants have done this due to the cheaper rate of lands available in rural areas. But these places lack good telecommunications and power infrastructure. Moreover, there are enough facilities to attract right human capital to such places. It’s better to have a data center in a city than a village. Read the complete article here:  http://www.cio.com/article/3036080/data-center/cities-not-cornfields-draw-data-centers.html

Predictive analytics and statistical analysis are based on the concept of relationships between observed and future actions. When analyzing people, we observe a small sample of data on people and build a predictive model to identify a number of shared traits they have. Micro-targeting is the idea of finding relationships among variables to recognize the target audience's shared traits. It helps to identify the right people. The steps included to predict purchase behavior and design a campaign to expand customer base are: 1. Create dataset. 

2.  Once we have a dataset loaded, we will analyze the people who have purchased the cloud solution and find what they have in common with one another. 

3.  To do this, our first step is to create a dependent variable. 

4. Then, we build a predictive model which takes that variable containing cloud purchase information, and compares it to other variables in our data set. 

5.  The regression model we build then compare our cloud purchase variable to whichever other variables used for analysis, and then gives us statistical correlations for each variable. 

6. Initiating the cloud solution licensing, then identify more people who fit this demographic.

For more read the full article at:

http://www.econtentmag.com/Articles/Column/Marketing-Master-Class/Why-Predictive-Analytics-and-Microtargeting-is-a-Game-Changer-for-Marketers-109377.htm

The most important issue in IT industry is a cyber - attack these days. Advanced security measures and sophisticated firewall systems are not free from bugs. Hence it is not difficult to crack complicated coding and launch a potential cyber-attack. Sometimes it is observed that these attacks take around one month time to get sorted out. So the question is how did these hackers are getting access to data of a particular company? The answer is simple, it's an in-situ type attack, i.e. hackers stay inside the firm and get familiar with encryption pattern, firewall dimensions and sophisticated filters. The solution is to identify these red flags. That can be only managed if all small potential deviations are identified and listed. These create a huge data pool which can be implemented to automate the alert system. By this process small attacks can be taken care off in no time and protect company from higher damage.

To read, follow: http://www.informationsecuritybuzz.com/articles/data-analytics-in-the-early-detection-of-cybercrime/

Network security consists of the policies adopted to prevent and monitor unauthorized access, misuse, alteration of computer network and network resources available. It also requires the authorization to access data in a network that is controlled by administrators. Users' needs to choose or assigned an Id and password and other information that allow them to access information and programs within their authority. Network security covers public and private computer networks, which are utilized in everyday jobs, conducting transactions and connection among business and government agencies and individuals and are involved in organizations, enterprises, and other institution. The most common and simple way to protect a network resource is by assigning it a unique name and a corresponding password.  To read more, read an article by Brendan Ziolo (Head of large enterprise strategy, Nokia): http://networkcomputing.com/net-security/security-starts-network/1250114547

Social media has changed the world, but has opened huge exposures for national security. With "Digital dust" trails, intelligence officers are vulnerable in many ways. CIA recruiters even found that the questions they asked in the interview are being posted online by candidates. But it is also helping investigators to solve cases using social media. Investigators are using social media even in undercover, covert and even in internal security operations. It is being suggested that some guidelines should be maintained for men and women who serve over country for social media utilization. To know more, please read the article by Philip Ewing (Writer at NPR) -: http://www.npr.org/2016/02/24/467933392/why-the-cia-likes-and-dislikes-social-media

In healthcare, information comes from multiple sources and it does exist in multiple forms like images, video, text, numerical data, multimedia, paper, electronic records or what not. These all are very important in the healthcare industry. Data mean the world to them.  So it is really necessary to have the right analytical tools to analyze such huge volumes of data. Moreover, jargons used in healthcare are often alien to patients or a layman. Inconsistent definitions, unstructured data is very hard to aggregate and maintain. Hence, if big data analytics used wisely can help save hundreds of billions every year. Read the complete article here: http://www.forbes.com/sites/sap/2016/02/22/can-big-data-analytics-save-billions-in-healthcare-costs/#4fdcfd7f6253

Few news organizations have developed "editorial analytics" approaches that move beyond the generic use. They develop a customized approach to analytics aligned with the specific editorial priorities. Editorial analytics differ from generic approaches in three ways.

First, editorial analytics are customized to the specific editorial priorities and organizational imperatives of a given organization. 

Second, editorial analytics are used to inform both short-term day-to-day decisions and long-term strategic development. 

Third, editorial analytics are always evolving to keep pace with a changing media environment. 

Editorial analytics represent a significant improvement in news organizations’ capacity to understand the media environment in which they operate. It also helps journalists to reach people.

For more read the article written by:  Federica Cherubini (Italian journalist and editorial researcher based in London) AND Rasmus Kleis Nielsen (director of research at the Reuters Institute for the Study of Journalism) at:

http://www.niemanlab.org/2016/02/the-next-step-moving-from-generic-analytics-to-editorial-analytics/

Chemical industry deals with lots of data sets. Some of these data are relevant to product development and the rest of them mostly helps to identify external parameters governing the production process. Generally, big data help to facilitate cost cutting issues. It brings a new product to the market and improves industry environment. Intellectual sensors are integrated with the research and material related informatics. This process minimizes the time required for new innovation. Sensitive sensors can also help to predict the upcoming situation by measuring current situations. Big data works in the back end. This ensures worker's safety by analyzing the toxic level, heart rate, etc. Intelligent sensors diagnose the past chemical data and all possible combinations to predict the new combination. It smoothens the R&D process. Therefore, automation, safety guide and intelligent forecasting are the key mantra for success in the chemical industry.

 To read, follow:  https://www.environmentalleader.com/2016/02/23/how-big-data-is-changing-chemical-manufacturing/ 

Big Data is massive. This article will explore the issues of big data: what it is, how it will improve decision - making, and how to use it correctly.

1) What's the big deal about big data?

Big data is all about three "V's" Velocity, Volume and Variety.

2) How it will improve decision?

# Deliver customer insights.

# Deliver targeted communication.

# optimize performance.

3) How to use it correctly?

# Collect data.

# Clean Data.

# Merge Datasets.

# Analyze Data.

To learn more about big data follow the article by Angela Hausman (PhD) at: http://www.business2community.com/big-data/big-data-like-teenage--01458960

It is the very beginning of the robotic revolution. The progress in this field is set to increase its pace. So this instills a fear what if these AI models grow smarter than those who created them. With AI applications covering up all your works, what is the purpose that it might leave you? The use of AI is growing fast in all the sectors. It is helping in improving the human living standards. There is a gap between the computers and human beings. But the upcoming AI models are focused to remove this gap. This will make computer - human interaction more like human like interaction. Read more about it in the article written by Damon Beres(Senior Tech Editor, The Huffington Post) at: http://www.huffingtonpost.com/entry/artificial-intelligence-mit-tech-conference_us_56cb20ade4b0928f5a6c7463?section=india

Silent customers create major risks to companies. They don't express their dissatisfaction. Companies can avoid these issues through the proper use of technology with predictive analytics.  Predictive analytics can stop the silent customer attrition by identifying four ways to retain customers:

1. Recognize customers who make a detailed analysis before they determine.

2. Determine the most effective actions to reduce the attrition

3. Distinguish between the best time, message, and channel to reach the customer.

4. Identify the full path to retention rather than one single action.

Companies that adopt predictive analytics to identify who is likely to leave and determine the best plan of action to stop attrition.

For more read :

http://www.information-management.com/news/big-data-analytics/using-predictive-analytics-to-stop-silent-customer-churn-10028295-1.html

Getting jobs these days are tuff. But, social media is helping people to get jobs. Here are some steps that you can follow to get a job -:

1. Set up strong profiles -: Create strong profiles on all social networking sites using short bio to show interest and skills for good online presences.

2. Start Networking -: Use social media to grow communication and professional network.

3. Get Recommended on LinkedIn -: Recommendations with positive references attract recruiters and manager.

4. Let Others Know You Are Looking -: Let your friends and relevant contacts know about what type of job you’re looking at.

5. Actively Seek Out Openings with Hashtags -: Use hashtags ‘#’ to search for relevant jobs.

6. Research Employers and Hiring Managers before Applying -: Social media profiles can be used as a research tool before applying for a job.

To know more, please read the article by Maria Onzain ( Writer at Tech.co) -: https://tech.co/steps-social-media-find-job-2016-02