SigmaWay Blog

Data science platform has become a buzzword of the decade. So, what is it? The sole purpose of a data science platform is to encapsulate all off-data science work by incorporating tools required to visualize, deploy, collect, analyze data, build models, generate reports. This toolkit makes it convenient to maintain, reproduce and scale up the project and produce results dynamically. Adoption of data science platforms is expected to grow almost double by 2018 as more companies realize its potential benefits. Many data driven business faces the challenge of effectively utilizing data science tools and lack integrated approach to their data science technology stack to find value in the data. While on the other hand, companies who have already established data science platforms are excelling in the field.

Read more at : http://dataconomy.com/2017/02/tech-wave-data-science-platforms/

The three critical steps involved in deployment of machine learning algorithm and exposing it to real world are :

Define a goal based on a metric : Decide if you want human level intelligence or an acceptable one as this decision will affect time and engineering cost of your system. Also define a metric to measure performance of your model.

Build the system : Build a minimum viable system without worrying much about accuracy. Then build an incremental strategy to improve your system by solving problems you face in each iteration.

Refine the system with more data : Initial metric values are not the indicators of real life, your data and users might change , so regularly monitor the system performance. Update it with new data and fine tune the model accordingly.

Read more at : http://www.erogol.com/short-guide-deploy-machine-learning/

Sometimes even the Machine learning algorithms behave so dumb that an image recognition model can be confused by generating an adversarial instance, i.e. by changing few pixels by either taking derivative of model output or exploiting genetic algorithms. Adversarial instances lie in low probability regions which is in contrast with limited instances of high probability regions from which the model was trained. A possible approach to solve this problem is ensemble training - To let multiple models back each other. As we look forward to developing more artificial intelligent systems it would become common to encounter such problems.

You can read more at: http://www.erogol.com/ensembling-against-adversarial-instances/

The emergence of massive unstructured data sources like Facebook and Twitter has created a need to develop distributed processing systems for Big Data Analytics. Hadoop (A Java based programming framework) has become the first choice of developers and industry experts mainly because its: Highly scalable, flexible, and cheap. An application is broken down into various small parts which runs on thousands of nodes to achieve fast computing speed and reduce overall operation time. Hadoop architecture continues to operate even if a node fails. Its incredible design allows you to process large volumes of data and extract computationally difficult features of users/customers.

Read more at : http://www.datasciencecentral.com/forum/topics/how-to-use-hadoop-for-data-science

Often the outputs of data models developed by data, scientists end up in a report which summarizes the state of business and used by stakeholders to make decisions. But it is necessary to achieve a system that can predict the future outcomes in real time. This can be done by integrating the model in a production environment, however, it requires advance engineering skills and data scientists cannot do it alone. The process of deployment follows broadly 7 steps :  1.Refactor the model code

2. Walk through the code and determine how it slots into the engineering cycle

3.Re-write into a production stack language or PMML

4.Implement it into the tech stack

5. Test performance

6. Tweak the model based on test results

7.Slowly roll out the model.

Today many companies are adopting tools to make this process faster to reap the benefit of data driven decision making.

Read more at : https://www.datascience.com/blog/navigating-the-pitfalls-of-model-deployment

E-Book business communities generate a lot of revenue everyday but sometimes it is difficult for author(s) to earn decent amount because of lack of preparation and research. No matter how unique and interesting your content is, if it doesn't appear on the first or second page of search results, it's highly unlikely that a visitor would ever read it. The story doesn't end here, one must cleverly select the title and cover which attract the reader as it changes the way we think. A neural network approach for the determination of most titles using Doc2Vec can be adopted to increase revenue. It involves training a thin two-layer neural network, which operates in unsupervised mode and form clusters of most similar words (using cosine similarity metric) based on context.

To read more about the technical implications here: http://www.datasciencecentral.com/profiles/blogs/use-neural-networks-to-find-the-best-words-to-title-your-ebook

In recent times, marketing has become an integral part of any business. Your business may offer the best products or services in the industry, but without continuous projection of the product to the customers, the chances of your competitors taking over your products is very high.

In the early 1950s and 1960s, marketing was production oriented and the quality of the production was the driving factor of marketing. Later, as new production technologies started to develop, techniques evolved simultaneously to meet the needs of the customers and efforts were made to maximize customization. But the next major advancement in marketing is literally hacking the brain of the customer.

Neuroscience is the field of study where the response to products and consumer decision-making is understood at the level of body and mind. The Neuromarketing concept is based on a model wherein the major thinking part of human activity, including emotion, takes place in the subconscious area that is below the levels of controlled awareness. For this reason, the perception technologists of the market are very tempted to learn the techniques of effective manipulation of the subconscious brain activity.

Neuromarketing is a flexible method to determine customer preferences and brand loyalty, because it can apply to anyone who has developed an opinion about a product or company.

To know more on neuromarketing, read : http://blog.fractalanalytics.com/integrated-marketing-effectiveness/neuroscience-in-marketing/

Starting a small business can seem tough and impossible at first when, there is so much to do on the front end before you even open the doors for your customers . We are now in the age of the art of technology which uses cloud computing to store all of our information and access if from anywhere we are. Not only does this make operating a business easier, but it makes the process much more efficient. The cloud can be your secret weapon to any aspect of the start-up process of your business. Here’s how.

Read more at:  http://www.business2community.com/cloud-computing/6-ways-use-cloud-start-business-01669177#o3OZvYPJyqBGeKit.99

Artificial intelligence (AI) could double annual economic growth rates by 2035 by changing the nature of work and ushering a new relationship between man and machine. The impact of AI technologies on business is projected to boost labour productivity by up to 40 percent by fundamentally changing the way work is done and reinforcing the role of people to drive growth in business.
 
“AI is poised to transform business in ways we’ve not seen since the impact of computer technology in the late 20^th century,” said Paul Daugherty, chief technology officer, Accenture, the primary company to have come up with this research result: “The combinatorial effect of AI, cloud, sophisticated analytics and other technologies is already starting to change how work is done by humans and computers, and how organizations interact with consumers in startling ways. Our research demonstrates that as AI matures, it can propel economic growth and potentially serve as a powerful remedy for stagnant productivity and labour shortages of recent decades.”

Read more on the research results of the AI impact at : https://newsroom.accenture.com/news/artificial-intelligence-poised-to-double-annual-economic-growth-rate-in-12-developed-economies-and-boost-labor-productivity-by-up-to-40-percent-by-2035-according-to-new-research-by-accenture.htm

Major Tech companies are all set to launch Vendor Security Alliance (VSA) - a new coalition committed to improve cyber security standards. The mission of VSA is to address cyber security risks and to establish cyber security standards that will help businesses to evaluate the security of third party vendors.This initiative is headed by Ken Baylor, Uber’s Head of Compliance. The VSA will work with top security experts and compliance officers and will release a yearly questionnaire to benchmark risk. The questionnaire aims to provide a standardized assessment that can be applied across different industries. It will enable companies to ensure that the other companies they are working with are secure. This will also save time and money that companies usually spend to evaluate the partners they work with. To read more about it, visit: http://www.infosecurity-magazine.com/news/uber-twitter-and-others-join-forces/

Back during the times of floppy disks and tapes, disaster and data recovery used to be two different aspects.  Creating data backups on tapes used to be time-consuming and a hectic job. The disk backup did ease the time-taking aspect, yet backup and recovery of data during times of emergency turned out a tedious task.

In today’s world, Cloud has changed the entire scenario. Not only does it allow data backup facilities, but disaster recovery as well. While off-site backups can take time to retrieve from storage and then deliver, instant Disaster Recovery from a cloud data centre means that anyone can  back up and run data in a matter of hours. This procedure is drastically reducing Recovery Time Objective (RTO) and other factors, as well as obliterating the threat of unstable network configurations or incompatible drives.

Read more at : http://www.business2community.com/cloud-computing/move-cloud-transformed-disaster-recovery-01660795#e0Kg4wwQuDLIAtlq.99

Whenever we talk about some advanced applications, we can see that we have moved way too ahead in the field of Artificial Intelligence (AI). Machine Learning (ML), a branch of AI, is a major factor to turn applications into intelligent ones. There are companies which are building such ML/AI technologies and others are incorporating ML/AI technologies in their applications and services to make it smarter and to provide customer better and easy facilities. But for the automated applications to provide better customer experiences, we need to have human beings in the loop. Although we have achieved great success in building many ML/AI applications, but we are still in the early stages of the journey. For more details, check the given link: https://techcrunch.com/2016/07/06/key-trends-in-machine-learning-and-ai/

The Turing Test, proposed by Alan Turing in 1950, is considered as a basic definition of Artificial Intelligence. It was used to see if something is a person or a machine. A computer passes the test if an interrogator cannot tell whether the answers come from a person or a computer. To pass a rigorously applied test, computer need to have certain capabilities like Natural Language Processing, Knowledge Representation, Automated Reasoning and Machine Learning.

But a recent study shows that the Turing Test has some limitations. Co-author Kevin Warwick, a computer scientist at Coventry University in England said that the Turing Test will not work in the case where the person or machine whoever is being interrogated chooses to stay silent. Read more about it at: http://www.livescience.com/55356-flaw-detected-in-turing-test.html

 Many a times we have observed companies quote data to support an argument to a statement. This however has been detrimental to the rise of data in general. How? Let us give an example. According to research it has been found that 2.5 quintillion bytes of data are created on a daily basis. Though that is a quintessential amount of data generation, but it is all the more astonishing to learn that 90% of this existing data has been already created in the last two years. The point is Big Data might be a huge hype in the industry, but the intelligent leaders should understand, that it is not the end-word. Big Data should be intelligently crafted with business strategies to provide desirable results.

To know and learn more, check out: http://www.business2community.com/big-data/biggest-mistake-companies-make-big-data-01645333#lClpgY4wJI7yodbO.97

We have come a long way from coding a simple calculator to programming robots to do our tasks. In the near future, we will be relying on robotic systems that are completely autonomous for tasks varying from driving a car to making life-death decisions like performing a surgery or prescribing medications. But the question arises “Are we ready to entrust the Robotic systems to make life-death decisions? Would we be able to program robots that understand the moral values, customs and rules by which we abide? Roboticists are figuring out the way to deal with the moral or behavioral problems that might arise with the robots. And hopefully, it will go great in the end. Read more at: http://spectrum.ieee.org/robotics/artificial-intelligence/can-we-trust-robots

Millennial refers to the population aged between 18 and 34. This makes up the largest chunk of mobile users, i.e. 85%. Thus technology consumption is the highest in this generation and CRM software can help brands to generate profit from this generation.

Social media is a powerful tool. Social media details are becoming more lucrative than communication methods and CRM stores these social media details in one place. It is a well known fact that almost all social media users search for product information and news from brands and also communicate with brands on social network. Most popular social media platforms are Facebook and Instagram.

Real time behavioral tools generate deeper insights into consumers’ purchasing pattern. These tools nowadays are available with CRM software. Real time data help to target precisely and also improves customer satisfaction.

Improving customer service is the key to success.  CRM software helps to track communications between customer and customer representatives and thus helps in resolving complaints promptly. 

To read more follow:- http://it.toolbox.com/blogs/insidecrm/3-ways-to-use-crm-to-target-millennials-74198

Content marketing when synced with CRM (customer relationship management) system increases profit throughout each phase of the sales cycle. There are 3 ways in which, uniting content marketing and CRM systems can generate higher sales.

1.       The case studies, applications and the customer testimonies provided by content marketing pieces bridges the gap between indecisions and confirmation of the customers.

2.       It is also important to keep updating the customers through recent customer successes, trade articles, new customer wins, product innovations, and the latest research. This results in portraying the company in front of the customer in a passive and informative way.

3.       The CRM systems should be used to let the sales department know when a new piece of content marketing is published. This closes down the gap between sales and marketing.

Thus content marketing plays a crucial role that helps to generate insight of a customer and ultimately creating a valuable partnership with the business. To read more follow:- http://it.toolbox.com/blogs/insidecrm/3-ways-crm-can-help-you-close-sales-with-content-marketing-74186

Many a times start-ups fail due to internal communication problems or lack of knowledge on work processes. Here customer relationship management (CRM) systems have an important role to play to manage and promote early growth of the businesses. Here are a few advantages of a CRM system for a start-up business:-

1. Access to automation process by an integrated CRM system saves time and money.

2. CRM is a beneficial tool for marketing as it can handle email marketing communications, following up with sales leads and continuing to promote the messages of the business.

3. CRM enables to tailor the data and make meaningful analysis for the businesses.

4. CRM provides a personalised first-class customer experience that makes a start-up unique from others.

To continue the business in the long run it is very important to have a service system that provides automation process, stores customer information and improves marketing efforts.

To read more follow: - http://it.toolbox.com/blogs/insidecrm/4-reasons-crm-systems-work-for-startups-74141

 To keep the data in electric form is much easier as it does not require physical space. Here are a few ways to keep a safe backup of business data:-

1.  USB flash storage is small gadgets and thus very useful to carry around big business data.

2. A hard drive provides a huge amount of storage, but they can easily break down when not handled properly.

3. Cloud storage is the most recently introduced storage options. It also provides large storage space and doesn’t require high IT knowledge.

4. A solid state drive is a revolutionary technology that offers incredibly high data transfer speeds.

5.A Great option for backing up data is the establishment of a local network. This makes backing up process fast, easy and secure. To use a combination of these solutions is the best way to keep the data safe and secure. To read more follow:-1.     http://it.toolbox.com/blogs/marketing-strategies/keeping-your-data-safe-5-available-storage-solutions-for-your-business-74118

In recent times game designing has become a very demanding job. Here are a few things required to be a good game designer:-

 Essential skills include basic knowledge of coding, solving problems and a have great encyclopaedic knowledge (i.e. they should be aware of different cultures, religions and philosophies).

Good communication skills are of utmost importance in this job. Collaborating and cooperating with teammates it is very important. The game designer is a mediator between the graphic designers and the story writers. Thus, it is essential to respect their ideas and vision.

Learning to take negative feedback is the key to success. The audience is the real judge of the game so their opinions about the game, whether positive or negative, should be taken sportingly.

Having a deeper insight into game mechanics is also crucial. It is important to know what elements are loved by people and which elements are to be avoided.

To read more follow:- http://it.toolbox.com/blogs/marketing-strategies/things-you-need-to-be-a-good-game-designer-74105