Modern needs of Big data consumption require data integration before data actually hit the business intelligence tools. This includes leveraging complex and unstructured data and enables raw data to flow securely through business. Today, even the smallest companies produce huge amount of data across systems which need to communicate with each other and therefore requires a platform to pipe all these data sources into Data Lakes.

Read more at: http://www.dataversity.net/dont-put-cart-horse-comes-big-data/

It has been evident that a great customer experience is one of the signs of a healthy business model. Machine Learning and Data Analytics are playing a fundamental role in building consumer intelligence systems. It is important to capture data and there is no single magic source to collect data. Telecoms are making billions by selling data. You need to ensure that the data is relevant to business. Once you have the right data, you are ready to model, design and engineer and deploy your 360-degree customer view platform and achieve the enhance customer experience for your organization.

You can read more at: http://www.datasciencecentral.com/m/blogpost?id=6448529%3ABlogPost%3A508502

Analytics is one of the of the most hot topic of the 21st century and it’s starting to become the second currency to  various organisation, but despite having so much knowledge we prone to create some blunders , they are broadly categorised as Data Visualization Errors (Erroneous Graphs) and Statistical Blunders.
Data Visualization Errors (Erroneous Graphs): This is one area that can give a nightmare to both the presenter as well as the audience. Incorrect data presentation can screw the intuition and can also lead to  misinterpretation of data by the audience and can leave the organisation with results which are practically useless for them.
Statistical Blunders Galore: This is probably a “no blunders zone” where one would not want to make false assumptions or erroneous selections and is easily one of the most error prone section. Statistical errors can be a costly affair to both the organisations as well as the audience, if not checked or looked into it carefully and hence must.
To know more read the full article by Sunil Kappal (author) at :http://www.datasciencecentral.com/profiles/blogs/the-most-common-analytical-and-statistical-mistakes

Data Science has become an inevitable charter in our everyday lives where every action of ours is measured, plotted, classified and logged. Businesses have also realized that they should adopt and embrace these changes now or risk being left behind in this fast moving digital world. Data Monetization is the new paradigm for organizations and slowly but steadily data is becoming their currency of trade.
Data Science is more like an art of turning data into actionable insights. Though we consume data regularly, we never cared to look behind the scenes on the rigorous processes, data preparation and machine learning algorithms that give us accurate data to devour. And this looks like some deep mystery but in reality it’s not a mystery, it’s just an intelligent use of data and various resources available to so called wizards: Data Scientists. To know more read the complete article by Prakash Pasupathy at: http://www.datasciencecentral.com/profiles/blogs/solving-the-data-science-mystery

In today’s digital age the world has become smaller.Gone are the days, when organizations used to load data in their data warehouse overnight and take decision based on BI, next day. Today organizations need actionable insights faster than ever before to stay competitive.With real-time analytics, the main goal is to solve problems quickly as they happen, or even better, before they happen. The lead role in revolutionizing real-time analytics is played by Internet of Things(IoT) . Now, with sensor devices and the data streams they generate, companies have more insight into their assets than ever before.
But it is so great as it looks , indeed it is as it helps getting the right products in front of the people looking for them, or offering the right promotions to the people most likely to buy using the real time recommender system.
are the days of waiting long hours to know the analytics of your data , now is the time to move beyond just collecting, storing & managing the data to take rapid actions on the continuous streaming data – Real-Time!! You can read the full article at http://www.datasciencecentral.com/profiles/blogs/do-you-know-what-is-powerful-real-time-analytics

Today world has become smaller and faster, with increasing computation speed decisions are done in seconds instead of days. Product information and comparison is available on any device any time. Real Time analytics involve solving problems quickly as they happen or even before they happen. Companies now have more insights into their assets. Several industries are using streaming data and putting real time analytics. The big data revolution has further accelerated the demand of real time analytics to analyze customer behavior. Gone are the days when decisions were based on data stored on a disk , actions are taken on streaming data. Read more at: http://www.datasciencecentral.com/profiles/blogs/do-you-know-what-is-powerful-real-time-analytics

A traditional data science department is comprised of Data Scientists, Data Engineers and Infrastructure Engineers. This model has a drawback that one role is always dependent on other and likely to criticize them for task failures because they didn't do their job well. These conflicts may reflect in the quality of final data product. So, what went wrong? You probably don't have big data. Jeff Magnusson (Director of Algorithms Platform at Stitch Fix) suggested a clever approach of forming a "High Functioning Data Science Department" which involves building an environment which allows autonomy, ownership, and focus for everyone involved yet at the same time clearly distinguishing the roles of Data Scientists and Data Engineers. Data scientist can't suddenly become talented engineers nor is that engineers will be ignorant of all business logic, the partnership is inherent to the success of this model. You can read more at: http://multithreaded.stitchfix.com/blog/2016/03/16/engineers-shouldnt-write-etl/

There is one traditional on-premises CRM and hosted CRM model. In traditional on-premises model, business owns and supports the software and hardware needed for the CRM solution and in hosted CRM model where CRM is purchased as a service for a monthly service fee. Both models have their own advantages and disadvantages. Generally, SME’s prefers hosted CRM and multinational companies prefer on-premises CRM system. Read more at: http://it.toolbox.com/blogs/insidecrm/hosted-vs-onpremises-crm-75321

Customers love personal touch and feeling special, whether it’s being greeted by name when we walk into the store, a shop owner remembering our birthday It make them feel like they are your single most important customer. But in an online world, you can’t guide them through the product they may like. This is where recommendation engines do a fantastic job.

With personalized product recommendations, you can suggest highly relevant products to your customers at multiple touch points of the shopping process. Intuitive recommendations make them feel like your shop was created just for them and hence they become your regular customers.

Application of Data Science to analyze the behavior of customers to make predictions about what future customers will like and understanding the shopper’s behavior on different channels can increase the sale by over 30%.Ultimately most important goal for any organisation is to convert visitors into paying customers and hence product recommendations are extremely important in digital age.You can read the full article on Product recommendations in Digital Age by Sandeep Raut (Author) at: http://www.datasciencecentral.com/profiles/blogs/product-recommendations-in-digital-age

In a short span of five years the world of analytics has changed immeasurably. Now we see fast analytics, interactive experimentation with data and exploratory analysis of data.

But why ? The answer to this question can be summed in three simple points. First, with fast analytics, it’s easier to keep up in an ever-changing world and keep pace with customers and market forces and businesses can see a measurable value from running advanced analytics on their data. Second, due to low prices of analytics businesses must meet customers’ expectations or risk losing them to a competitor. Third, it has the ability to elevate a company to the next level and provide it with a competitive edge over its rivals through the real-time insights it can achieve.

And , hence every one in this competitive market is shifting to advance analytics. To know more you can read the article by Aaron Auld (CEO of EXASOL) at: http://www.datasciencecentral.com/profiles/blogs/the-rise-of-advanced-analytics .

According to a recent study, it was found that mobile CRM applications boosted productivity on an average of 15%, 30% of the respondents reported productivity boosts of 20% or more. In another survey, 81% of CEOs believe mobile technology is strategically important. Use of mobile helps in better communication which in turn helps in better customer service. It also helps the sales staff with more marketing insights on the go instead of being tied to the desktop while researching the prospect and updating on the status of the relationship between client and company. Read more at: http://it.toolbox.com/blogs/insidecrm/using-mobility-to-boost-crm-75304

In modern business, organization must sell in a smart way by using CRM tools as CRM lets you organize information, keep track of prospects, also helps predict what the customers will buy and when they are likely to purchase it. It also acts as a control to make sales efforts more effective and in turn gives valuable information from sales campaigns to individual customers. Read more at: http://it.toolbox.com/blogs/insidecrm/sell-smarter-not-harder-with-crm-75292

Robo-advisers are automated advisers with provide financial advisory as low cost, so it’s available to everyone. The costs are as low as 1 euro. They open the door to the financial markets and give you the possibility to invest in stocks, bonds and other securities and keep their costs low by trading Exchange-Traded Funds.

But, how do they exactly work ?? Robo-advisors use algorithms based on mean-variance optimization, a mathematical framework to create a portfolio of assets such that the expected return is maximized for a given level of risk. Financial market data is used to estimate expected return, standard deviation and correlation for every asset class. On opening an account, you are asked simple questions about your age, income, savings and willingness to take risk. This data is collected to estimate your risk tolerance and fit their model to your current situation and preferences and give you the best advice to invest in the market. To know more read this article http://www.datasciencecentral.com/profiles/blogs/robo-advisers-and-the-future-of-financial-advice by Stefan.

Aim-Lever-Data-Implement (ALDI) is an approach to integrate marketing analytics with Data Science, i.e making data the primary object of various decisions. So is it something very difficult or some kind of rocket science , no it’s a simple paradigm which follow the following approach :

• Aim :

The aim of the analysis needs to be fixed by the strategy teams, before any data scientists gets involved, as they are are ones who know what exactly is needed.

• Lever :

It is very important for an organization to know what actions it is going to take as a result of the analysis, not what the organization’s strengths are.

• Data :

Once the objectives have been defined the next step is then to gather the appropriate data and then perform the analysis. This is where data scientists would really come in.

• Implement :

This is the final step of the problem where results from analysis are used to make further decision on how the problem is going to be tackled and what all needs to be done by the various departments.

You can read the full article by Srividya Kannan Ramachandran at http://www.datasciencecentral.com/profiles/blogs/aldi-a-new-paradigm-for-integrating-marketing-analytics-with-data

Yes, if companies need anything in 2017 they are Data Scientists.

But why , what is so special about them? And the answer is :

Data scientists tracks millions of data sets and provides concrete information for organizations looking to break their data into meaningful information that can be used at all levels in the organization.

As this is the data century , every company wants to recommend its users what they are most likely to choose and hence the need of Data Scientists to study the data and extract various pattern from it and hence creating a 360-degree view of their customers. This not only impresses the customers but also helps the companies in understanding their customers better and hence improving their services according to the customers.

So , in a nutshell yaa companies do need Data Scientists.

You can read more at  http://www.datasciencecentral.com/profiles/blogs/why-large-companies-need-data-science-experts-like-you

What is dark data ? The large amount of data collected by companies that goes useless due to lack of analysis(39%) or structure(25%) or even sometimes due to lack of proper tools(13%) is known as the dark data. If used/analyzed properly gives a new dimension to the companies.

But how can we harness the dark data. Well it’s no rocket science , just some simple measures and you have a whole new dimension of data.Here are just a few of them :-

• Keep a track of user logins and various checkout at different locations, this helps in creating a 360-degree view of the user.

• Mobile phone data, this will help to illuminate an array of new product and marketing opportunities, and hence improve marketing effectiveness.

• Free text input, such as feedback can be analysed to determine if general sentiment of the feedback is positive or negative.

Data when properly harnessed can be a powerful and can serve as a gateway to new insights, developing new opportunities and boosting your business into the data-driven century.

You can read more at http://www.datasciencecentral.com/profiles/blogs/dark-data-the-billion-dollar-opportunity

Data Science is one of the hottest job of the 21st century. But is it easy to be a data scientist , and the answer is it’s not hard. But here are some of the things that one need to avoid to be a bad data scientist :

• Focus on tools rather than business problems :

Yaa tools do matter, but what is even more important is the problem you are working on, it should be the basis of all your decisions.

• Planning communication last :

Communication helps in getting various insights about our ideas and hence help in improving our approach to handle a particular problem.

• Data analysis without a question / plan :

Data without a plan or motive is useless and we often end with more of the things we don’t need than the things we really need.

• Don’t read enough :

This is a mistake that everyone makes, to be updated with the recent development tends helps in constantly improving our skill set and hence benefits the organization.

• Fail to simplify :

Data Scientist generally fail to maintain the core idea behind their product and hence end upwith something which is much complicated for the end users.

• Don’t sell well :

The job of data scientist doesn’t end with creating the product , he must know how to sell it, how to reach to the end users.

You can read more at http://ucanalytics.com/blogs/6-worst-mistakes-for-data-scientists-and-how-to-avoid-them-explained-with-quotable-quotes/

Data Analytics is the science of examining raw data with the purpose of drawing conclusions from it. In today’s environment, where data driven business decisions are the norm, becoming familiar with data analysis tools and techniques is key to professional growth.

According to market sources, India will face a demand supply gap of 2,00,000 analytics professionals between 2016-19.

So, get trained in data analytics…Understand data driven application design, accelerate your learning curve, engage your customers well, improve your ROI and gain competitive advantage.

Sigmaway presents its Data Analytics training in Delhi, India, for those who think it is worth exploring a career in Analytics.

Gain from the experience of the best in class – With over 25 years of combined experience, our trainers have used the power of data analytics and generated huge benefits for clients.

Content: Hands on exercises on RapidMiner to understand Data Analytics tools and concepts; Case studies to emulate industry applications. Topics covered include Text Mining, Web Mining, Fraud Analytics, Decision Trees and Sentiment Analysis.

For details, contact: trainings@gosigmaway.com or visit: http://www.gosigmaway.com/events/analytics/24-data-analytics-training-delhi-india-7-8-january-2017  to register.

Date: 7th & 8th January, 2017, DELHI, India

Eligibility: No pre-requisites. Students need ID proof to avail discount

Certification: Training certificate provided on training completion.

Investment for Students: Rs. 3,000 + 15% tax

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Early bird discounts also available! And progressive discounts for Groups (conditions apply)

Maintaining a good relationship with customers is the most important thing in any business. Promises made to customers must be fulfilled. The CRM system can help in this area by reminding you the details of your interactions with customers and also can remind you of the details of all your contacts with the customer, i.e. everything from the initial sales calls to follow-up and service work. Read more at: http://it.toolbox.com/blogs/insidecrm/giving-customers-what-they-want-with-crm-75060

Nowadays, mobile CRM is important for businesses. Data theft is a serious issue for any organization. This article explores some of the steps that an organization need to protect your business from the hazards of data theft. They are: Encryption of data, set strong passwords, track laptops with remote software, and you must be able to wipe files from mobile devices if they are stolen or lost. Read more at: http://it.toolbox.com/blogs/insidecrm/mobile-security-with-crm-75054