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15 Python Tips : How to Write Code Effectively

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 Here are some Python tips to keep in mind that will help you write clean, efficient, and bug-free code.     Python Tips for Effective Coding 1. Code Readability and PEP 8  Always aim for clean and readable code by following PEP 8 guidelines.  Use meaningful variable names, avoid excessively long lines (stick to 79 characters), and organize imports properly. 2. Use List Comprehensions List comprehensions are concise and often faster than regular for-loops. Example: squares = [x**2 for x in range(10)] instead of creating an empty list and appending each square value. 3. Take Advantage of Python’s Built-in Libraries  Libraries like itertools, collections, math, and datetime provide powerful functions and data structures that can simplify your code.   For example, collections.Counter can quickly count elements in a list, and itertools.chain can flatten nested lists. 4. Use enumerate Instead of Range     When you need both the index and the value in a loop, enumerate is a more Pyth

3 Top Books to Read for Data Analytics

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The financial domain has openings for analytics jobs. The top financial domains are Banking, Payments, and credit cards.  The skills you need to work in data analytics are SAS, UNIX, Python, and JavaScript. I have selected three books for beginners of data analysts. The Best Books are on: SAS UNIX Python  3 Top Books to Read for Data Analytics 1. SAS best book  I found one best book that is little SAS . This covers examples and complex macros you need for your job. The best-selling Little SAS Book just got even better. Readers worldwide study this easy-to-follow book to help them learn the basics of SAS programming. Now Rebecca Ottesen has teamed up with the original authors, Lora Delwiche, and Susan Slaughter, to provide a new way to challenge and improve your SAS skills through thought-provoking questions, exercises, and projects. 2. UNIX book The  basic commands you will get everywhere . The way of executing Macros or shell scripts is really what you need. This is a good b

Big data benefits in Education field- A data driven approach

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Netflix can predict what movie you should watch next and Amazon can tell what book you'll want to buy. With Big Data learning analytics, new online education platforms can predict which learning modules students will respond better to and help get students back on track before they drop out. (Big data Hadoop career) That's important given that the United States has the highest college dropout rate of any OECD (Organisation for Economic Co-operation and Development) country, with just 46% of college entrants completing their degree programs. In 2012, the United States ranked 17th in reading, 20th in science, and 27th in math in a study of 34 OECD countries.The country's rankings have declined relative to previous years. Many students cite the high cost of education as the reason they drop out. At private for-profit schools, 78% of attendees fail to graduate after six years compared with a dropout rate of 45% for students in public colleges, according to a study by

Social Media and Mobile Technology for Health care

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(People also click these jobs to  know skill set  and to apply  even from your phone!!) The ubiquity of mobile phone accessibility around the world is increasing. Worldwide the number of mobile phones in use grew from fewer than 1 billion in 2000 to around 6 billion in 2012. Recent estimates conclude that over 75% of the world' s population have access to a mobile phone (World Bank, 2012). Globally, there has been a rapid rise in the use of smart phones by consumers with over 1 billion Smart Phones subscribers (Approximately 30% of smartphone users are likely to use wellness apps by 2015, (Bjornland, Goh, Haanæs, Kainu, & Kennedy, 2012) with more than 30 billion mobile applications being downloaded in 2011 (World Bank, 2012). Along with this increase in penetration, there has been a significant increase in the development and deployment of mobile software applications across multiple computing platforms (e.g. smart phones, tablets and laptops). The most pop

Big Data: Top Cloud Computing Interview Questions (1 of 4)

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The below are frequently asked interview questions on Cloud computing: 1) What is the difference between Cloud and Grid? Grid: -Information service -Security Service -Data management -Execution Manageement Cloud: - Maintains up-to-date information of resources -Create VMs according to user requirement -Application deploment -User management 2) What are the different cloud standards? -Interoperability standards -Security standards -Portability Standards -Governance and Risk standards 3) What are the two different sub-systems in Cloud computing ? -Management sub system -Resource sub system 4)What is Cloud compouting? The promise of cloud computing is ubiquitous access to a broad set of applications and services, which are delivered over the network to multiple customer. 5) Why we need specialized network for Cloud services? The public Internet is the simplest choice for delivering cloud-based services. In this model, the cloud provider simply purchases Inter

Predictive Analytics - A Case Study

Nishad Sharma, a Delhi-based entrepreneur, is a typical online shopper who keeps a tab on the various sales and promotional deals run by e-commerce companies from time to time. On the cool Delhi evening of February 4, he opened online fashion company Myntra's app on his smartphone to see if there were any deals on trousers. That day, Myntra was running its Rush Hour sale in which customers could avail up to 50 per cent discount on select products. After filtering his search, Sharma decided to add a pair of UCB trousers to his shopping cart. Predictive Analytics But then he changed his mind. Perhaps he could get a better deal if he logged on into a sale on a weekend. To his surprise, Sharma received a mail from Myntra next morning, telling him what he presumably lost by abandoning his cart the previous day. The same product was now available at a 100 per cent mark-up. To close the sale, the company sent another mail to Sharma a couple of days later, offering a smaller discount of 20

Analytics on Fly - Read It

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The basis for real-time analytics is to have all resources at disposal in the moment they are called for . So far, special materialized data structures, called cubes, have been created to efficiently serve analytical reports. Such cubes are based on a fixed number of dimensions along which analytical reports can define their result sets. Consequently, only a particular set of reports can be served by one cube. If other dimensions are needed, a new cube has to be created or existing ones have to be extended. In the worst case, a linear increase in the number of dimensions of a cube can result in an exponential growth of its storage requirements. Extending a cube can result in a deteriorating performance of those reports already using it. The decision to extend a cube or build a new one has to be considered carefully.  In any case, a wide variety of cubes may be built during the lifetime of a system to serve reporting, thus increasing storage requirements and also maint

Major Trends in IT in 2015

As per research paper submitted by Gartner, the following trends will dominate in IT industry. Advanced, Pervasive and Invisible Analytics: Analytics will take center stage as the volume of data generated by embedded systems increases and vast pools of structured and unstructured data inside and outside the enterprise are analyzed. "Every app now needs to be an analytic app," said Mr. Cearley. "Organizations need to manage how best to filter the huge amounts of data coming from the IoT, social media and wearable devices, and then deliver exactly the right information to the right person, at the right time. Analytics will become deeply, but invisibly embedded everywhere ." Big data remains an important enabler for this trend but the focus needs to shift to thinking about big questions and big answers first and big data second — the value is in the answers, not the data. Cloud/Client Computing: The convergence of cloud and mobile computing will continue

Accenture Sees Demand in Big Data Analytics

Accenture Plc., which has 40% of its global big data analytics team based in India, plans to tap the country’s high-end analytics market in anticipation of an increase in demand driven by the government’s Digital India programme.  The National Democratic Alliance (NDA) government’s Digital India initiative is aimed at delivering government services electronically in urban and rural areas, cutting out human intervention and closing the gap between digital haves and have-nots.  It will act as an umbrella plan to integrate and synchronize all digital initiatives including the national broadband plan and the domestic manufacturing policy. “Big data analytics will play a major role in the whole digital disruption that is happening in India today,” said Arnab Chakraborty, managing director for advanced analytics at Accenture Digital.  “Mobility has leapfrogged in India and the whole ‘Make in India initiative’ has caught up strongly in the last six to eight months with the new leadership co

These are energy analytics top areas to focus

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Energy Analytics is a new area started recently. The below are the key points in analytics. According to Siemens, Outsource your energy data management as a service and benefit from regular analyses performed by our energy experts. Evaluations show that this service makes it possible to easily achieve savings potential of as much as 5 percent. Headlines of energy analytics Market Forecast: Energy Data & Analytics Energy Data Management & Analytics Business Skills Big Data in an Utilities Environment: Real Case Studies Advantages of Big Data & Analytics: Smart Metering & Cloud Computing Innovative Solutions & Technologies Data Analytics in a Smart Grid Perspective - DONG Energy Case Study Big Data in the TSO Business Achieving Benefits From Smart Meters Deployment With Advanced Analytics - Return on Experience From Large Scale Deployments in the US Smart Grid Cybersecurity, Frameworks and Standards Adopting Open Source Software in Energy Anal