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The Eclectic Mix of Big Data and Marketing

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Marketers with even rudimentary knowledge of Big Data are better placed to precisely reach the largest amount of potential target customers than their counterparts who are uninitiated to the world of Big Data. Good marketers know the customers they target very well. Big Data facilitates this process.

The collection of data and its storage into separate data banks is simply a process part in acquiring raw data. This data should be reproduced in such a manner that marketers are able to easily grasp. And with the impending explosion of IoT devices, the amount of data too is expected to increase by leaps and bounds.

Marketers need to analyze the data available to them very carefully. The process involved is a complicated one which requires the use of specialized software tools.

This is where a translation management system comes into play. These tools may readily be used in order to get the desired insight from the vast pool of data available. Applications like these have made the process so simple that some people who are using it on a daily basis are even unaware that they are dealing with Big Data.

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Big Data Uses in Marketing

  • Honing Market Strategy Through Monitoring Trends Online

You may use tools as simple as Google Trends to keep abreast of the latest trends in the world of the internet. With a number of ways to customize and filter the results marketers have an easy access of that is trending at any instant and associate the product in ways that let it have increased traction.

  • Define Customer Profiles With Big Data

It is a good idea to consult Big Data while drawing up your ideal profile of customers. There is no more need to make educated guesses with things as they stand of today. Through the use of Big Data marketers have access to the various details like demographics, age, work profile of the consumers they target. The case study of the Avis Budget may be cited where it was found that Big Data facilitated the formation of an effective contact strategy.

  • Engaging the Buyer at the Correct Time

Timing, according to some marketers, of the essence when it comes to marketing. This process too is facilitated by Big Data which makes relevant and timely marketing strategies possible. We may take the case of displaying mobile ads at timings when the customer is most like to be online.

  • Content That Boosts Sales

Big Data also lets marketers know the content that gives them the extra edge when it comes to marketing their products. Some of the tools used in translation management make such an analysis possible with scores on individual pieces of content. Success and efficiency of assets both may be gauged through the use of such tools. With the required information marketers will be able to pinpoint content that customers liked.

  • Predictive Analysis

If the base CRM information of a particular company and other providers of Big Data is taken into account the marketer may get a predictive lead score which in turn may be used to make an accurate prediction of the behavior of leads in the future. The end result is that marketers acquire an indication of considerable clarity on their digital behaviors and should be taken into account more when considering lead scoring.

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Now, do not both of them make up an eclectic mix.

 

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How Data Scientists Take Their Coffee Every Morning

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How Data Scientists Have Their Coffee

To a data scientist we are all sources of data, from the very moment we wake up in the morning to visit our local Starbucks (or any other local café) to get our morning coffee and swipe the screen of our tablets/iPads or smart phones to go through the big headlines for the day. With these few apparently simple regular exercises we are actually giving the data scientists more data which in-turn allows them to offer tailor-made news articles about things that interest us, and also prepares our favorite coffee blend ready for us to pick up every morning at the café.

The world of data science came to exist due to the growing need of drawing valuable information from data that is being collected every other day around the world. But is data science? Why is it necessary? A certified data scientist can be best described as a breed of experts who have in-depth knowledge in statistics, mathematics and computer science and use these skills to gather valuable insights form data. They often require innovative new solutions to address the various data problems.

Data Science: Is It the Right Answer? – @Dexlabanalytics.

As per estimates from the various job portals it is expected that around 3 million job positions are needed to be fulfilled by 2018 with individuals who have in-depth knowledge and expertise in the field of data analytics and can handle big data. Those who have already boarded the data analytics train are finding exciting new career prospects in this field with fast-paced growth opportunities. So, more and more individuals are looking to enhance their employability by acquiring a data science certification from a reputable institution. Age old programs are now being fast replaced by new comers in the field of data mining with software like R, SAS etc. Although SAS has been around in the world of data science for almost 40 years now, but it took time for it to really make a big splash in the industry. However, it is slowly emerging to be one the most in-demand programming languages these days.What a data science certification covers?

Tracing Success in the New Age of Data Science – @Dexlabanalytics.

This course covers the topics that enable students to implement advanced analytics to big data. Usually a student after completion of this course acquires an understanding of model deployment, machine language, automation and analytical modeling. Moreover, a well-equipped course in data science helps students to fine-tune their communication skills as well.

Keep Pace with Automation: Emerging Data Science Jobs in India – @Dexlabanalytics.

Things a data scientist must know:

All data scientists must have good mathematical skills in topics like: linear algebra, multivariable calculus, Python and linear algebra. For those with strong backgrounds in linear algebra and multivariable calculus it will be easy to understand all probability, machine learning and statistics in no time, which is a requisite for the job.

More and more data-hungry professionals are seeking excellent Data Science training in Delhi. If you are one of them, kindly drop by DexLab Analytics: we are a pioneering Data Science training institute. Peruse through our course details for better future.

 

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Using Hadoop Analyse Retail Wifi Log File

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Since a long time we are providing Big Data Hadoop training in Gurgaon to aspirant seeking a career in this domain.So, here our Hadoop experts are going to share a big data Hadoop case study.Think of the wider perspective, as various sensors produce data. Considering a real store we listed out these sensors- free WiFi access points, customer frequency counters located at the doors, smells, the cashier system, temperature, background music and video capturing etc.

 

big data hadoop

 

While many of the sensors required hardware and software, a few sensor options are around for the same. Our experts found out that WiFi points provide the most amazing sensor data that do not need any additional software or hardware. Many visitors have Wi- Fi-enabled smart phones. With these Wifi log files, we can easily find out the following-

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5 Online Sources to Get Basic Hadoop Introduction

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Basic Hadoop Courses

Big data Hadoop courses are hitting it big in the world of business whether it is healthcare, manufacturing, media or marketing. Data is generated everywhere, and Hadoop is a readily available open source Apache software program that can be utilized to crunch and store Big Data sets.

As per reports from the Transparency Market Research the forecast shows a promising growth opportunity from the existing USD 1.5 million back in 2012 to USD 20.8 million within 2018. These promising growth numbers suggest that there will be an increased need for human resources to manage, develop and oversee all the Hadoop implementations.

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Many experts believe that one can learn any new subject by simple self-study if only you invest enough time and sincere predisposition towards a topic. After all self-study is actually what a person does to acquire knowledge about any given topic. Be it how to fix a leaky faucet or learn a new language or learn strum a guitar. Studying is on one’s own in any case. But to be an expert in a given field, you have to study on your own while you also need to invest your energy in the right direction. And to know the right direction, you need a mentor or a guide to lead the way.

But if you want to test the waters, and tinker with Hadoop to understand its basics, you can go through the wide range of documents available at the Apache Hadoop website for your perusal. Also try downloading the Hadoop open source release to get the feel of the program while tinkering with different features.

Here are 5 online sources where you can seek some basic introduction to Hadoop for big data:

  1. IBM’s open sources, Hadoop Big Data for the Impatient is a good option to go through the basics of Hadoop. It also offers a free download of Hadoop image (you might need Cloudera) to help you work with examples of Hadoop-based problems. You will also be able to get an idea of Hive, Oozie, Pig and Sqoop. The course is available in Vietnamese, Chinese, Spanish and Portuguese.
  2. Cloudera offers a Cloudera essentials course for Apache Hadoop. Apache Hadoop chapter wise video tutorials are available with Cloudera essentials. But this course is mainly targeted at administrators and those who are well-acquainted with data science, to update their skills on the subject.
  3. YouTube also offers a long list of videos on Hadoop topics for beginners. Some are good while others may not be so helpful for the Hadoop virgins. Simply type Hadoop and you will find a never-ending list of videos related to Hadoop. Some are quite useful for clarifying simple doubts related to Hadoop.
  4. Udemy is another site where you can get some free videos as well as a few for a fee. Simply put Hadoop free on the search bar at their homepage and see what comes up.
  5. Udacity was developed by Silicon Valley giants like FaceBook, Cadence, Twitter and the likes. They offer a 14-day free trial with free course materials. But you will need to pay for the course if you do not finish the course within 14 days.

 

Seeking a good and reliable Hadoop training in Delhi? When DexLab Analytics is here, why look further! Being a recognized Big Data Hadoop institute in Gurgaon, the courses are truly interesting.

 

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Big Data And The Internet Of Things

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The data that is derived from the Internet of Things may easily be used to make analysis and performance of equipment as well as do activity tracking for drivers and users with wearable devices. But provisions in IT need to be significantly increased.Intelligent Mechatronic Systems(IMS) collects on an average data points no fewer than 1.6billion on a daily basis from automobiles in Canada and U.S.

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The data is collected from hundreds of thousands of cars that have on board devices tracking acceleration, the distance traversed, the use of fuel as well as other information related to the operation of the vehicle.This data is then used as a means of supporting insurance programs that are based on use.Christopher Dell, IMS’s senior director recently stated they they were aware that the data available were of value, but what was lacking is the knowledge on how to utilize it.

But in the August of 2015, after a project that lasted for a year, IMS added to its arsenal a NoSQL database with Pentaho providing tools related to data integration and analytics. This lets the data scientists of the company increased flexibility to format the information. This enables the team of analytics to make micro analysis of the driving behavior of customers so that trends and patterns that might potentially enable insurers to customize the rates and policies based on usage.

In addition to this the company further is pursuing an aggressive growth policy through asmartphone app which will further enhance its abilities to collect data from vehicles and smart home systems making use of the Internet of Things.Similar to the case of IMS, organizations that look forward to analyze and collect data gathered from the IoT or the Internet of Things but often find that they need an upgrade of their IT architecture. This principle applies to enterprise as well as consumer sides of the IoT divide.

The boundaries of business increasingly fade away as data is gathered from fitness trackers, diagnostic gears, sensors used in industries, smartphones. The typical upgrade includes updating to big data management technologies like Hadoop, the processing engine Spark,NoSQL databases in addition to advanced tools of analytics with support for applications drivenby algorithms. In other cases all it is needed for the needs of data analytics is the correct combination of IoT data.

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Join DexLab Analytics’ Big Data certification course and kick start your career in the rapidly developing sector of data science.

 

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Sure shot Ways to Crack Big Data Interviews

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Sure shot Ways to Crack Big Data Interviews

If you are a Big Data analyst looking for open position in the entry to mid level range of experience then you should prepare yourself with the following resources in your arsenal before you storm an interview with all guns blazing.

  • Adequate Expertise of Analytical tools like SAS for the processing of data

Make sure that you assign most of the time you have set aside for the preparation of your upcoming interview to brush up your knowledge regarding the tools of analytics that are relevant in your context. Ensure that you acquire proficiency in the analytics tool of your choice. For positions of junior levels the importance of expertise with a particular analytical tool like Hadoop, R or SAS cannot be overstressed. In such circumstances the focus centers around data preparation and processing. It is highly advisable that you review concepts related to the import and manipulation of data, the ability to read data even if it not standard say for example data whose input file types are multiple in number and mixed data formats. You also get to show off your skills at efficiently joining multiple datasets, selecting conditionally the observations or rows of data, how to go about heavy duty data processing of which SQL or macros are the most critical.

  • Make a Proper Review of End to End Business Process

This is most relevant towards candidates who have prior experience at working in the Big Data and Analytics industry. Prior experience inevitably gives rise to interviewers wanting to know more about the responsibilities that you shouldered and your role in the business process and how you fitted in the context of the broader picture. You should be able to convey to the interviewer that the data source is understood by you along with its processing and use.

  • A solid concept of the rudiments of statistics and algorithms

Again this tip is also for those with prior experience. Recruiters seek to know whether you are aware of issues likely to be faced by you while you confront problems regarding data and business. Even freshers are expected to know the fundamental concepts of statistics like rejection criteria, hypothesis testing outcomes, measures of model validation and the statistics related assumptions that a candidate must know about in order to implement algorithms of various sorts. In order to crack the interview you must be prepared with adequate knowledge of concepts related to statistics.

  • Prepare Yourself with At Least 2 Case Studies related to Business

The person on the other side of the interview table will undoubtedly try to make an assessment about your knowledge as far as business analytics is concerned and not solely to the proficiency you command in your tool of choice. Devote time to review projects on analytics you already have worked on if you have prior experience. Be prepared to elucidate on the business problem, the steps that were involved in the processing of data and the algorithm put into use in the creations of the models and reasons behind, and the way the results of the model was implemented. The interviewer might also ask about the challenges faced by you at any stage of the whole process, so keep in mind the issues faced by you in the past and their eventual resolution.

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  • Make Sure that Your Communication Remains Effective

If you are unable to effectively communicate then no much diligent preparations you make, they will be of no use. You can try out mock interviews and answering questions that the recruiter might ask. Spare yourself of the trouble of framing effective answers at the moment when the question is asked during an interview. Though you perhaps will be unable to anticipate each and every question, nevertheless but prior preparation will result in better and more coherent answers.

 

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The Pros and Cons of HIVE Partitioning

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The Pros and Cons of HIVE Partitioning Hive organizes data using Partitions. By use of Partition, data of a table is organized into related parts based on values of partitioned columns such as Country, Department. It becomes easier to query certain portions of data using partition.

Partitions are defined using command PARTITIONED BY at the time of the table creation.

We can create partitions on more than one column of the table. For Example, We can create partitions on Country and State.

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Syntax:

CREATE [EXTERNAL] TABLE table_name (col_name_1 data_type_1, ….)

PARTITIONED BY (col_name_n data_type_n , …);

Following are features of Partitioning:

  • It’s used for distributing execution load horizontally.
  • Query response is faster as query is processed on a small dataset instead of entire dataset.
  • If we selected records for US, records would be fetched from directory ‘Country=US’ from all directories.

Limitations:

  • Having large number of partitions create number of files/ directories in HDFS, which creates overhead for NameNode as it maintains metadata.
  • It may optimize certain queries based on where clause, but may cause slow response for queries based on grouping clause.

It can be used for log analysis, we can segregate the records based on timestamp or date value to see the results day wise / month wise.

Another use case can be, Sales records by Product –type , Country and month.

 

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THE BIGGER THE BETTER – BIG DATA

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One fine day people realized that it is raining gems and diamonds from the sky and they start looking for a huge container to collect and store it all, but even the biggest physical container is not enough since it is raining everywhere and every time, no one can have all of it alone, so they decide to just collect it in their regular containers and then share and use it.

Since the last few years, and more with the introduction of hand-held devices, valuable data is being generated all around us. Right from health care companies, weather information of the entire world, data from GPS, telecommunication, stock exchange, financial data, data from the satellites, aircrafts to the social networking sites which are a rage these days we are almost generating 1.35 million GB of data every minute. This huge amount of valuable, variety data being generated at a very high speed is termed as “Big Data”.

 

 

This data is of interest to many companies, as it provides statistical advantage in predicting the sales, health epidemic predictions, climatic changes, economic forecasts etc. With the help of Big Data, the health care providers, are able to detect an outbreak of flu, just by number of people in the geography writing on the social media sites “not feeling well.. down with cold !”.

Big data was used to locate the missing Malaysian flight “MH370”. It was Big Data that helped analyze the million responses and the impact of the very famous TV show “Satyamev Jayate”. Big data techniques are being used in neonatal units, to analyze and record the breathing pattern and heartbeats of babies to predict infections even before the symptoms appear.

As they say, when you have a really big hammer, everything becomes a nail. There is not a single field where big data does not give you the edge, however processing of this massive amount of data is a challenge and hence the need of a framework that could store and process data in a distributed manner (the shared regular containers).

Apache Hadoop is an open source framework, developed by Doug Cutting and Mike Cafarella in 2005, written in java for distributed processing and storage of very large data sets on clusters of normal commodity hardware.

It uses data replication for reliability, high speed indexing for faster retrieval of data and is centrally managed by a search server for locating data. Hadoop has HDFS (Hadoop Distributed File System) for the storage of data and MapReduce for parallel processing of this distributed data. To top it all, it is cost effective since it uses commodity hardware only, and is scalable to the extent you require. Hadoop framework is in huge demand by all big companies. It is the handle for the Big hammer!!

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