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

Nowadays, marketers are giving importance to customer journey mapping. They also talk about customer journey and how they can reach decision makers at the right point of the customer journey. Customer Journey Maps are useful as they describe an ideal customer engagement model from the customer’s perspective and can also help us to understand the customer story of various specific customers. Many marketers are putting emphasis on enterprise customer architecture and its ability to successfully support customer experience regardless of the particular journey that the customer is on. Read more at:  http://it.toolbox.com/blogs/integrate-my-jde/customer-experience-initiatives-customer-journey-vs-customer-architecture-70937

The internet of things (IoT) is coming in a big way. This means that in a few years’ time, almost everything you own or do will be connected to or available on the internet in some way. The security of information must be built into the IoT, otherwise it will be chaos. This article covers three things that we need to consider with regard to security of information. Read more at: http://it.toolbox.com/blogs/datasecurity/security-in-the-internet-of-things-70940

Vendor Managed Inventory (VMI) programs are often used in coordination with Just-In-Time Delivery initiatives and Direct Store Delivery. A vendor managed inventory program can reduce inventory costs and risks. So, not all enterprise software systems set-up to deal with VMI. A VMI program involves a supplier, a customer, consigned goods and non-consigned goods and both customer-side and supplier-side ERP, logistics, WMS and supply chain systems often need integration in order to function properly. For VMI being effective, information needs to be as fresh. Information based on bar-code scanning and mobile devices is therefore important for any businesses that rely on VMI. Read more at: http://it.toolbox.com/blogs/integrate-my-jde/integrating-systems-to-support-vendor-managed-inventory-70946

Two main goals of Agile Sprint are building new functionality and building new knowledge. Building new functionality seems obvious for sprints, but teams also need to focus on building knowledge.  Each sprint should end smartly from its inception.  A UI designer should focus on both of these goals. Within a sprint, a UI designer helps in coding and testing of his/her design while simultaneously, he/she focuses on the next design feature to be built. A UI designer's top priority should be working in the current sprint. If a developer or tester needs any clarification regarding the design than he/ she should immediately halt the work and attend to their queries. But then one might say that every member of the team does so. Be its analysts, architects, database designers. The difference lies in the amount. Designers spend majority of time in building knowledge. To know more, read the article by Mike Cohn (founder of Mountain Goat Software), at: https://www.mountaingoatsoftware.com/blog/incorporating-ui-design-in-scrum-sprints

A customer visits your site or product, checks the available options and services offered. Then he decides to go along with you or not.  Good business policy is to give a personal touch to each customer so that they feel at home each time. But taking care of their needs at each step becomes a time taking process if done manually. On the other hand automation makes it more smooth and effective. If CRM is practiced along with automation, it sets everything into a correct perspective.

Read more about it in the article written by Inside-CRM at http://it.toolbox.com/blogs/insidecrm/five-ways-marketing-automation-and-crm-go-together-like-peanut-butter-and-jelly-70904

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

Generally, product owners' role is to tell WHAT TO BUILD instead of HOW TO BUILD it. But there are some situations when product owner must specify some architectural decisions. Let's consider a scenario, years ago; when Sun was looking for the ways to promote Java, they paid companies who made certain applications using Java. But, such decisions should not be taken regularly. Product owner can decide what hardware pieces to be used to make the product economically viable. So product owner can dictate architectural decisions, but they should take good care and should make decisions sparingly, wisely and ideally. To know more, read the article by Mike Cohn (founder of Mountain Goat Software), at: https://www.mountaingoatsoftware.com/blog/can-a-product-owner-dictate-the-architecture

If customer experience is better then only customer will be loyal to the brand and according to many surveys, customer experience improves sales. Thus, investing in improving customer experience is not typically an investment, but a sales opportunity. It becomes more important in case of online websites as there are a limited number of interactions to impress the customer. Word-of-mouth is a significant and cheapest source of marketing that directly affect the targeted audience. This reputation of a firm is affected by a customer’s experience. So to conclude, improved customer experience will result in improved sales, better reputation and loyal customers. Read more at: http://www.business2community.com/customer-experience/invest-improving-customer-experience-01418769#WJErvfXdbvlskeWL.97

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/

If we talk about the recent past, machine learning was only used by a few who understood the algorithms and had access to very huge amount of data on which to employ it. But with the evolution of big data technology becoming a commodity and algorithms easier to use, machine learning has moved out of the hands of the few to the hands of the citizen developers and regular users. Four key steps taken in 2015 for the development of the machine learning are:-

# learning became easier to use.

# Everyone and their brother released a machine learning library or toolkit. 

#Big data to feed machine learning also became cheaper and easier.

#The label “machine learning” was applied to way too many items.

Read more at: http://www.infoworld.com/article/3017250/application-development/4-great-leaps-machine-learning-made-in-2015.html

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

Agile teams must embrace change. After all, that is what agile means, right? Accommodating changing customer's requirement… But the stakeholders or customers must also understand that nothing comes for free in the world. So are changes. They have a cost related to them. Scrum works on a rule that once the required changes are fully stated, a sprint begins. And no changes are allowed into a sprint. Once a sprint is started, it’s not disturbed and the team’s entire focus is on selected work. This is good and works efficiently, but can sometimes backfire. The customer can question that the foundation of being agile is to welcome changing requirements. Well, yes, but they aren’t free. Customers must understand that changes introduced beyond a certain point have a cost related to them. And both the customers and organization should work together to optimize results with the minimum cost.To know more, read the article by Mike Cohn (founder of Mountain Goat Software), at: https://www.mountaingoatsoftware.com/blog/change-isnt-free

Every project starts with a Software requirement Specification (SRS) document, but somewhere in the middle a decision to adopt agile methods is made. So the question arises whether an SRS can serve as agile's product backlog? Let's find out. An SRS is a document with all the direct or indirect requirements of the system are listed. It generally has statements like "The system shall.."

Whereas product backlog serves two purposes: 1. It lists the work that is to be done and 2. It prioritizes the work to be done. It is different with the SRS in the sense that SRS only tells about what work which is to be done, not the priorities. So just for the sake of adopting agile, SRS should not be mixed with user stories, instead a product backlog should be created which will serve the purpose well. To know more, read the article by Mike Cohn (founder of Mountain Goat Software), at: https://www.mountaingoatsoftware.com/blog/can-a-traditional-srs-be-converted-into-user-stories#

It's all about customer experience - make it better using Data Driven Marketing! It's important to treat them like true customers by taking them through personalized life cycles. Normally, customers are expected to feed the website with lots of data regarding their preferences and personal details. So there is a lot of data in the hand of an owner. But the value lies in effectively scaling data and analytics to enrich their journey. Thus, planning the marketing strategies by keeping in focus the results of this data analytics. The article written by Kevin Lindsay digs deeper into the power of Data Driven Marketing at: http://blogs.adobe.com/digitalmarketing/personalization/strength-in-numbers-best-practices-for-data-driven-marketing/

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/