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Showing posts from May, 2014

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SQL Interview Success: Unlocking the Top 5 Frequently Asked Queries

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 Here are the five top commonly asked SQL queries in the interviews. These you can expect in Data Analyst, or, Data Engineer interviews. Top SQL Queries for Interviews 01. Joins The commonly asked question pertains to providing two tables, determining the number of rows that will return on various join types, and the resultant. Table1 -------- id ---- 1 1 2 3 Table2 -------- id ---- 1 3 1 NULL Output ------- Inner join --------------- 5 rows will return The result will be: =============== 1  1 1   1 1   1 1    1 3    3 02. Substring and Concat Here, we need to write an SQL query to make the upper case of the first letter and the small case of the remaining letter. Table1 ------ ename ===== raJu venKat kRIshna Solution: ========== SELECT CONCAT(UPPER(SUBSTRING(name, 1, 1)), LOWER(SUBSTRING(name, 2))) AS capitalized_name FROM Table1; 03. Case statement SQL Query ========= SELECT Code1, Code2,      CASE         WHEN Code1 = 'A' AND Code2 = 'AA' THEN "A" | "A

These Lovely Skills You Need to Enter as Data Architect

We can analyze data quickly now. The data can be any size. The basic skills you need are R language skills and Machine learning for analyzing the data. MapReduce Techniques The MapReduce techniques and parallel processing in Hadoop allow us to cheaply and efficiently implement MapReduce on Internet scale problems. We use SQL like tools Pig and Hive. NoSQL We analyze so-called NoSQL storage solutions exemplified by HBase for their critical features: speed of reads and writes, data consistency, and ability to scale to extreme volumes. Data Architect Requirements Data architects develop, analyze and administer data for businesses, schools and other organizations. They need sophisticated design and development skills to collect data and translate it for use in computer applications and systems. Most data architects have a bachelor's degree in information technology (IT), as well as years of experience in the IT field. Experience with programs such as Microsoft Excel, Ac

Top Companies Who Need Data Analysts

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The following list of companies hiring analytics candidates. Companies Recruting Analytics Firms Amazon.com Bill and Melinda Gates Foundation INVISTA Nordstrom PopCap Games Salesforce.com Starbucks T-Mobile Tacoma Housing Authority Target

Data Science Real Advantages to Read Today

Real business solution you can get from data science analysis. Your sales is the main requirement. No sales means no business. Data Analytics helps to boost your organization sales. Real Advantages of Data Science My presentation here gives you complete business picture of data analytics , and skills companies expecting from analytics team. Data analytics -The data can be from web, user devices, own databases and Social media AI -Delivering products based on artificial intelligence Big data -Data of any format and you need to make ready for analysis. You can understand patterns of people You can explore current market You can explore solutions to Agriculture You can show answers to weather Predicting the disaster like earth-quake  Data Analytics what else you can read Data Analytics from Srinimf | Tech.Jobs. Biz.Success Also Read Uses of Data Analytics from HBR

India is gearing for awesome Data Analytics Jobs

There is no surprise in India, all companies started building Data analytics team and infrastructure. With a lot of Indian companies building their data analytics team, the requirement in the domestic market for this skill will increase over the next couple of years. The requirement for Data Analytics  There will be an increased demand for data analytics professionals. Industry experts believe that currently big data and analytics is one of the top three skills in demand in India.  Organizations are looking at their internal set of data to understand the business better – as a result, there will be an explosion of various job opportunities in this area. Top three segments where huge demand for data analytics engineers are Data Science, Statistics, Technical specialists with multiple skills. Top Demand Roles in Data Analytics Some of the requirements are for tech personnel, statistician, econometrician, data scientist, analytical consultant, functional consultant, etc

Retail Analytics Solution from Leader in Data Science SAS

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Retail market is changed now. So many companies now open shops across the world. Every business owner tries to increase sales. This is possible with analytics. Retail Analytics The study also includes an in-depth look at how best-in-class retailers use analytics, as well as the business analytics software vendor landscape. Walmart started retail business in India. So the real use of data analytics started now. References Download here

5 Key Ideas on SAS Banking Analytics

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SAS is providing solutions for banking. Getting away with financial crime just got harder. The latest SAS Financial Crimes Suite arms institutions to detect potential suspicious activity more efficiently than ever. A new customer due diligence solution within the suite more accurately detects changes in a customer’s risk profile. Enhanced anti-money laundering and case management capabilities also make it easier to have a complete view of threats across an institution’s financial crimes investigation unit. “A comprehensive view of potential threats will help in efforts to thwart criminals from successful attempts of hiding illicit funds,” says James Wester, global payments research director at IDC Financial Insights.  “A technology infrastructure with customer risk rating and high-performance analytics will help speed detection and investigation in all channels.”. SAS Analytics Suite for Banking Crimes Today’s rigorous regulatory environment requires banks to move quickly

IBM these are analytics solutions offering to different industries

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Every industry has its own particular big data challenges. Banks need to analyze streaming transactions in real time to quickly identify potential fraud. Utility companies need to analyze energy usage data to gain control over demand.  Retailers need to understand the social sentiment around their products and markets to develop more effective campaigns and promotions. Analytics solutions help organizations take control of big data and uncover the insights they need to make the best decisions. IBM has Analytics Solutions in various lines: Banks: Apply analytics to improve customer experiences and operational efficiency, and integrate risk into daily decision making. Communication:Uncover insights about customers, network performance and market trends to make better business decisions. Retail: Build lifetime customer relationships by meeting demands for innovative products while containing costs. Education: Make more informed decisions to improve student performance an

Hyderabad Based Startup Built Largest Ever Big data Electoral Repository

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I was gone through an email from my friend saying that they are creating a Hadoop project to analyze voters data. This project in my view is both academic and research oriented. The real challenge was extraction of voter info from 2.5 crore PDF pages and translation of the same into English to fuse with other sources. The technology was a big hurdle.  Hadoop Project The infrastructure, built especially for the project, included 64 node Hadoop, PostgreSQL and servers that process a master file containing over 8 Terabytes of Data. Besides, Testing and Validation was another big task. ‘First of a Kind’ Heuristic (machine learning) algorithms were developed for people classification based on name, geography etc., which help in the identification of religion, caste, and even ethnicity. Data from Sources “Data from multiple sources like census, economic and social surveys were mapped to polling booths. Simultaneously, external and propriety data sources had to be fused wit

Career Opportunities to Write Algorithms

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Many participants in the Analytics seminar expressed opportunity in preparing algorithms for predictive analytics. You Need Algorithms Why Using these algorithms, businesses can make better data-driven decisions by extracting actionable patterns and detailed statistics from large, often cumbersome data sets. Many business people small to big expecting some kind of algorithms. So that they can save their precious time in predictive analytics. As per IBM What are Good Benefits of Right  Algorithm Transform data into predictive insights to guide front-line decisions and interactions.  Predict what customers want and will do next to increase profitability and retention.  Maximize the productivity of your people, processes and assets.  Detect and prevent threats and fraud before they affect your organization.  Measure the social media impact of your products, services and marketing campaigns.  Perform statistical analysis including regression analysis, cluster analysis and

Google Analytics - Training.PDF

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Google Analytics can track data from a shopping cart on your own or other, domains with the addition of some code. If your website initiates a purchase checkout process on a separate store site (for example, if you send customers from www.mystore.com to www.securecart.com), you just have to add some tracking code to your store site and the shopping cart pages on the host site. The specific code can be found in the Analytics Help Center in the article titled, “How do I use Google Analytics to track a 3rd-party shopping cart?” Read more here: http://static.googleusercontent.com/media/www.google.com/en//grants/education/Google_Analytics_Training.pdf

Top Skills You need for Data Science Engineers

Data science job is not straight forward coding job. But coding is part of it. You need both Technical and business skills to be successful. Responsibilities Dealing with internal customers Getting data from multiple data sources Dealing with Admins of lot other databases Preparing reports with Tableau More: R for Data science with real time examples Qualifications: Lot of coding skills needed Positive attitude Innovative way of problem solving Degree in engineering Lot of business knowledge

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

I have 8 Years Experience in IT. How I Can Move Into Analytics Career

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You have now great experience in Information Technology. Still you are looking for change. The reason is data analytics is growing field, and applying in many fields .

Business Vs Demographic Vs Product Analytics

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List of top analytics areas and their differences 1. Analytics in Business Advertising Analytics Brand Analytics Promotion Analytics Business-to-business marketing Analytics Social Media Analytics Tracking Studies 2. Demographic Analytics Consumer Analytics Concept Testing Data Mining Customer Satisfaction Study Analytics Demographic Analytics Employee Satisfaction Analysis Text Mining Ethnographic Analytics Media Testing Opinion Polling and Predictive Analytics Usage & Attitude Studies Segmentation Analytics Semiotic and Cultural Analysis 3. Product Analytics Packaging and Design Effectiveness Analytics New Product Development Pricing Studies Product Testing Scenario Planning  Also Read Top IT Skills You Need to Become Data Analyst