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5 Steps to Reassess Your Big Data Business Strategy

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5 Steps to Reassess Your Big Data Business Strategy

Company employees at all levels need to understand the role of big data in planning business strategies. Strategic planning has to be dynamic- constantly revised and aligned with the current market trends.

As the first quarter of 2018 is nearing to its end, here are 5 domains every business needs to pay attention to:-

  • Information retention for field-based technology:

In the current tech-driven business world, a lot of information needs to be collected from field-based technologies, like drones and sensors. Owing to internet bandwidth constraints, this data has to be stored locally instead of transmitting them for collection in a central location. Bandwidth constraints affect cloud-based storage systems too. Thus, companies need to restore traditional practices of distributed data storage, which involve collecting data locally and storing them on servers or disks.

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  • Collaboration with cloud vendors:

Cloud hosting is popular among businesses, especially in small and midsized enterprises. Onsite data activities of companies include maintenance of infrastructure and networks that ensure internal IT access. With the shift towards cloud-based applications, businesses need to revise disaster recovery plans for all kinds of data. It should be ensured that vendors adhere to corporate governance standards, implement failover if needed, and SLAs (Service Level Agreements) match business needs. It is often seen that IT strategic plans lack strong objectives pertaining to vendor management and stipulated IT service levels.

  • How a company defines ROI:

In the constantly evolving business scenario, it is necessary to periodically re-evaluate the ROI (return on investments) for a technology that was set at the time of purchasing it. Chief information officers (CIOs) should regularly evaluate ROIs of technological investments and adjust business course accordingly. ROI evaluation should be a part of IT strategic planning and needs to be revisited at least once a year. An example of changing business value that calls for ROI re-assessment is the use of IoT technology in tracking foot traffic in physical retail stores. At a point of time, this technology helped managers display the most desirable products in best positions within a store. With the shift of customer base from physical to online venues, this tech has become redundant in terms of physical merchandising.

  • How business performance is assessed:

Like shifting ROIs, KPIs (key performance indicators) for companies that are based on inferences drawn from their data, are expected to change over time. Hence, monitoring these shifting KPIs should be a part of a company’s IT strategic plan. For example, customer engagements for a business might shift from social media promotions to increased mentions of product defects. Therefore, to improve customer satisfaction, businesses should consider reducing the number of remanufacture material authorizations and IoT alerts for sensors/devices in the production processes of these goods.

  • Adoption of AI and ML:

Artificial intelligence and machine learning play major roles in the current technological overhaul. Companies need to efficiently incorporate AI-powered and ML-based technologies in their business processes. Business leaders play key roles in identifying areas of a business where these techs could add value; and then testing their effectiveness through small-scale preliminary projects. This should be an important goal in the R&D strategic planning of business houses.

Let’s Take Your Data Dreams to the Next Level

As mentioned in Harvard Business review, ‘’the problem is that, in many cases, big data is not used well. Companies are better at collecting data-about their customers, about their products, about competitors-than analyzing the data and designing strategy around it.’’

‘’Used well’’ means not only designing superior strategies but also evolving these strategies with changing market trends.

From IT to marketing- professionals in every sector are going for big data training courses to enhance their competence. Enroll for the big data Hadoop certification course in Gurgaon at DexLab Analytics– a premier data analyst training institute in Delhi.

 

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AI is enhancing careers: How can you gain advantage in this AI-era?

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Artificial intelligence has a significant impact on our lives. Several AI powered automation tools are already in use such as customer service applications and voice-powered assistants, like Apple’s Siri and Amazon’s Alexa. Adoption of AI will benefit the business by improving the quality and consistency of work. Based on a discussion between Forbes Agency council members, we have listed the ways in which artificial intelligence can help workers improve their career.

  1. More valuable insights

AI will bring positive changes in the job of PR professionals. AI technology will take over manual jobs such as news monitoring, researching, reporting and making media lists. AI based predictive analytics will help PR professionals make better market predictions. They will reduce manual workload and help in strategic and creative thinking.

  1. Replace mundane tasks

AI, automation and machine learning will replace daily low-quality cognitive tasks such as scheduling calendar invites, daily food ordering, determining whether to answer/review/delete emails based on facts. They will eventually aid in quality tasks such as identifying connections, analyzing correlation and drawing inferences.

  1. Act as concierge

Popularity of Alexa, Watson, and Einstein suggest that consumers will expect tech to provide concierge services in the future. As AI techs evolve post their purchase, it will anticipate an individual’s daily tasks and provide highly personal recommendations.

  1. Make marketing smarter

AI will enable companies develop stronger relationships with their customers. IBM’s Watson and other cognitive technology will help analyze unstructured text, audio, images and video. AI’s ability to perceive and process personality, tone and feelings will help deliver better personal recommendations. It will help companies carry out conversations using chatbots.

  1. Automate customer support

The availability of chatbots round the clock will save a lot of time. They answer customer questions, give recommendations and guide customers to the next step. They will reduce the workload of customer support systems. Bots can draw insights on the needs, engagements and emotions of customers.

  1. Unleash the full potential of your mind

Workers will be spared from carrying out mundane tasks. They will have the time to focus on productive tasks, which require problem-solving skills and creativity.

  1. On-the–fly video editing

AI will eventually edit videos in real time.  Real- time user engagement will perform multiple instantaneous tasks such as changing sound effects on the fly.

  1. Create jobs and assimilate workflow

AI will interfere with regular workflow but in return it will create new jobs. It will help integrate the workforce. Humans will be instrumental in helping the AI work in harmony with the employees.

  1. Improve future strategies

Humans will always be a part of the PR industry, as they are crucial in maintaining a healthy customer relationship. The data that is collected through AI will enable making more informed decisions for the future. AI will help companies stay abreast of information related to their competitors through better media monitoring.

  1. Shrink 40 hours of analysis to 4 minutes

Manual analysis is very time consuming. The future of marketing efficiency lies in automation tools that will drastically reduce the time taken to analyze data and form strategies.

  1. Productivity even during commute

AI has made automated driving a reality. Driving in autopilot mode greatly reduces driver fatigue and can affect productivity during commute, especially to and from work.

  1. Improve brand engagement

AI can help devise customized experiences in real time. It interprets customer interactions and instantly creates customized content.

  1. Make routine processes easier

Entrepreneurs describe AI as the ultimate efficiency driver. The day to day tasks can be entrusted to digital hands, which enable human hands to be more productive. AI driven technology is benefitting manufacturing processes as well as advertising platforms.

  1. Give edge in competition

Businesses using AI will have a competitive edge over their clients. This is because AI implementation replaces manual processes of sorting complex data, drawing key insights and chalking out an action plan. AI improves decision-making, ROI, operational competence and cost savings.

AI related employment opportunities are on the rise. Compared to the demand, there is a lack in the number of professionals proficient in AI. It is predicted that by 2020, 20 percent of companies will need their workers to monitor and direct neural networks. About 2 million jobs in the cyber security sector are about to go vacant in the coming years.

So it is absolutely imperative to future-proof your career for the imminent AI era. Broaden your skill set and increase your proficiency by taking professional training in Machine Learning, Business Analytics and Data Science. Get an edge in your career by joining the Data science and machine learning certification course offered by Dexlab Analytics- a premier institute offering multiple courses on data science.

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5 Examples that Show Artificial Intelligence is the Order of the Day of Daily Life

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Artificial Intelligence is no more an elusive notion from science fiction; in fact, it’s very much in use in everyday life. Whether you realize it or not, the influence of AI has grown manifold, and is likely to increase further in the coming years.

5 Examples that Show Artificial Intelligence is the Order of the Day of Daily Life

Here are a few examples of AI devices that lead you to a brighter future. Let’s have a look:

Virtual Personal Assistants

The world around you is full of smart digital personal assistants – Google Now, Siri and Cortana though available on numerous platforms, such as Android, Ios and Windows Mobile strives to seek meaningful information for you, once you ask for it using your voice.

In these apps, AI is the power giver. With the help of AI, they accumulate information and utilize that data to better understand your speech and provide you with favorable results that are tailor-made just for you.  

Smart cars

Do you fantasize about reading your favorite novel, while driving to office? Soon, it might be the reality! Google’s self-driving car project and Tesla “autopilot” characteristic are two latest innovations that have been stealing the limelight lately. In the beginning of this year, there was a report that, Google developed an algorithm that could potentially allow self-driving cars learn the basics of driving just like humans, i.e. through experience.

Fraud detection

Have you ever found mails asking if you have made any particular transaction using your credit card? Several banks send these kinds of emails to their customers to verify if they have purchased the same to avoid frauds being committed on your account. Artificial Intelligence is employed to check this sort of fraud.

Like humans, computers are also trained to identify fraudulent transactions based on the signs and indications a sample shows about a purchase.

Buying pattern prediction

Distinguished retailers, like Amazon do make a lot of money, as they anticipate the buyer’s needs beforehand. Their anticipatory shipping project sends you products even before you ask for them, saving you from the last-minute online shopping. If not online retailers, brick-and-mortar retailers also use the same concept to offer coupons; the kind of coupons distributed to the shoppers is decided by a predictive analytics algorithm.

Video games

Video games are one of the first consumers of AI, since the launch of the very first video games. However, over the years, the effectiveness and intricacies of AI has doubled, or even tripled, making video games more exciting, graphically and play wise. The characters have become more complex, and the nature of game-play now includes a number of objectives.

No matter, video games are framed on simple platforms, but as industry demand is burgeoning at an accelerating pace, a huge amount of money and effort are going into improving AI capabilities to make games more entertaining and downright exciting!

Fact: Artificial Intelligence is serving millions of people on earth today. Right from your smartphone to your bank account, car and even house, AI is everywhere. And it is indeed making a huge difference to all our lives.

To gain more knowledge on AI, enroll in Big Data Certification Gurgaon by DexLab Analytics. Their big data and data analytics training is of high quality and student-friendly. The prices of the course are also fairly convenient.

The blog has been sourced from – https://beebom.com/examples-of-artificial-intelligence

 

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R Programming, Python or Scala: Which is the Best Big Data Programming Language?

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R Programming, Python or Scala: Which is the Best Big Data Programming Language?

For data science and big data, R, Python and Scala are the 3 most important languages to master. It’s a widely-known notion, organizations of varying sizes relies on massive structured and unstructured data to predict trends, patterns and correlations. They are of expectation that such a robust analysis will lead to better business decisions and individual behavior predictions.

In 2017, the adoption of Big Data analytics has spiked up to 53% in companies – says Forbes.

The story of evolution

To start with, big data is just data, after all. The entire game-play depends on its analysis – how well the data is analyzed so as to churn out valuable business intelligence. With years, data burgeoned, and it’s still expanding. The evolution of big data mostly happened because traditional database structures couldn’t cope with such multiplying data – scaling data became an important issue.

For that, here we have some popular big data programming languages. Dive down:

R Programming

R Programming is mainly used for statistical analysis. A set of packages are available for R named Programming with Big Data in R (pbdR), which encourages big data analysis, across multiple systems via R code.

R is robust and flexible; it can be run on almost every OS. To top that, it boasts of excellent graphical capabilities, which comes handy when trying to visualize models, patterns and associations within big data structures.

According to industry standards, the average pay of R Programmers is $115,531 per year.

For R language training, drop by DexLab Analytics.

Python

Compared to R, Python is more of a general-purpose programming language. Developers adore it, because it’s easy to learn, a huge number of tutorials are available online and is perfect for data analysis, which requires integration with web applications.

Python gives excellent performance and high scalability for a series of complicated data science tasks. It is used with high-in-function big data engines, like Apache Spark through available Python APIs.

Their Machine Learning Using Python courses are of highest quality and extremely student-friendly.

Let’s Take Your Data Dreams to the Next Level

Scala

Last but not the least, Scala is a general-purpose programming language developed mainly to address some of the challenges of Java language. It is used to write Apache Spark cluster computing solution. Hence, Scala has been a popular programming language in the field of data science and big data analysis, in particular.

There was a time when Scala was mandatory to work on Spark, but with the proliferation of many API endpoints approachable with other languages, this problem has been addressed. Nevertheless, it’s still the most significant and popular language for several big data tools, including Finagle. Also Scala houses amazing concurrency support, which parallelizes a whole many processes for huge data sets.

The average annual salary for a data scientist with Scala skills is $102,980.

In the end, you can never go wrong with selecting any one of the big data programming languages. All of them are equally good, productive and easy to excel on. However, Python is probably the best one to start off with.

For more updates or information on big data courses, visit DexLab Analytics.

The original article is here at – http://www.i-programmer.info/news/197-data-mining/11622-top-3-languages-for-big-data-programming.html

 

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How Big Data Plays the Key Role in Promoting Cyber Security

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The number of data breaches and cyber attacks is increasing by the hour. Understandably, investing in cyber security has become the business priority for most organizations. Reports based on a global survey of 641 IT and cyber security professionals reveal that a whopping 69% of organizations have resolved to increase spending on cyber security. The large and varied data sets, i.e., the BIG DATA, generated by all organizations small or big, are boosting cyber security in significant ways.

How Big Data Plays the Key Role in Promoting Cyber Security

Business data one of the most valuable assets of a company and entrepreneurs are becoming increasingly aware of the importance of this data in their success in the current market economy. In fact, big data plays the central role in employee activity monitoring and intrusion detection, and thereby combats a plethora of cyber threats.

Let’s Take Your Data Dreams to the Next Level

  1. EMPLOYEE ACTIVITY MONITERING:

Using an employee system monitoring program that relies on big data analytics can help a company’s human resource division keep a track on the behavioral patterns of their employees and thereby prevent potential employee-related breaches. Following steps may be taken to ensure the same:

  • Restricting the access of information only to the staff that is authorized to access it.
  • Staffers should use theirlogins and other system applications to change data and view files that they are permitted to access. 
  • Every employee should be given different login details depending on the complexity of their business responsibilities.

 

  1. INTRUSION DETECTION:

A crucial measure in the big data security system would be the incorporation of IDS – Intrusion Detection System that helps in monitoring traffic in the divisions that are prone to malicious activities. IDS should be employed for all the pursuits that are mission-crucial, especially the ones that make active use of the internet. Big data analytics plays a pivotal role in making informed decisions about setting up an IDS system as it provides all the relevant information required for monitoring a company’s network.

The National Institute of Standards and Technology recommends continuous monitoring and real-time assessments through Big Data analytics. Also the application of predictive analytics in the domain of optimization and automation of the existing SIEM systems is highly recommended for identifying threat locations and leaked data identity.

  1. FUTURE OF CYBER SECURITY:

Security experts realize the necessity of bigger and better tools to combat cyber crimes. Building defenses that can withstand the increasingly sophisticated nature of cyber attacks is the need of the hour. Hence advances in big data analytics are more important than ever.

Relevance of Hadoop in big data analytics:

  • Hadoop provides a cost effective storage solution to businesses.
  • It facilitates businesses to easily access new data sources and draw valuable insights from different types of data.
  • It is a highly scalable storage platform.
  • The unique storage technique of Hadoop is based on a distributed file system that primarily maps the data when placed on a cluster. The tools for processing data are often on the same servers where the data is located. As a result data processing is much faster.
  • Hadoop is widely used across industries, including finance, media and entertainment, government, healthcare, information services, and retail.
  • Hadoop is fault-tolerant. Once information is sent to an individual node, that data is replicated in other nodes in the cluster. Hence in the event of a failure, there is another copy available for use.
  • Hadoop is more than just a faster and cheaper analytics tool. It is designed as a scale-out architecture that can affordably store all the data for later use by the company.

 

Developing economies are encouraging investment in big data analytics tools, infrastructure, and education to maintain growth and inspire innovation in areas such as mobile/cloud security, threat intelligence, and security analytics.

Thus big data analytics is definitely the way forward. If you dream of building a career in this much coveted field then be sure to invest in developing the relevant skill set. The Big Data training and Hadoop training imparted by skilled professionals at Dexlab Analytics in Gurgaon, Delhi is sure to give you the technical edge that you seek. So hurry and get yourself enrolled today!

 

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How Data is Found Influencing Political Campaigns Online

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How Data is Found Influencing Political Campaigns Online

Data is and has always been the heart and blood of politics. In the 21st century, digital transformation has hit politics hard. Ambitious politicians and lobbyists invest hundreds of dollars on framing potential campaigns and agendas: in the past US presidential elections, as much as $5 billion dollars was spent, if not less, out of which estimated $1 billion was set aside for digital advertising alone.

Online information has already started weaving a change in perspective of people. They tend to manipulate us. Few are even of the notion that big data is being used to develop customized political advertising that challenges our rational minds and change our voting pattern. But do you think it’s true? Can data have that kind of intense impact?

Cambridge Analytica Data Breach

In the wake of Facebook and Cambridge Analytica data breach, where data of 50 million Facebook users were compromised, a compelling issue of data safety and protection has come to the forefront of our conscience. Cambridge Analytics is a British political consulting firm that works by integrating data mining, data analysis and brokerage with strategic communication for successful electoral processes.

A recent terrifying revelation suggested that this company has used Facebook users’ confidential data to predict personalities and then tailor personalized advertizing according to their psychological attributes. For years, this company has been performing data analysis services strategizing various presidential campaigns for US and UK. This March, the data analytics firm has been alleged to have harvested information from more than 50 million Facebook users without their knowledge to build a system for targeting US voters. The employees of the firm were also found boasting about using fake news, fabricated sex scandals and cheap tricks to swing electoral campaigns across the globe and this has created a big uproar in the industry.

From this, anyone can fathom the power of data in politics and framing opinions. Digital technologies have become a powerful tool for both positive and negative change. Technology remains remote, pivotal and paternalist. The political systems are changing, and so are we. That’s why it’s high time for all of us to be cautious, prudent and have a voice of our own.

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How to Enhance Online Campaign Success Legally

While social media scores high, email actually pulls the reigns, when it comes to raising funds for political campaigns online.

Mitt Romney’s 2012 campaign revealed about 70% donations came through emails.

During the Obama campaign, the figures were as high as 90% to be precise.

Besides raising funds online via email, integration of myriad digital marketing channels with smart data is crucial to rally in unconditional support on behalf of candidates.

Here are ways to boost your online campaign success:

  • Mobile ads – Increase relevancy for micro-targeted audience
  • Actionable TV – Using set-top-box information, particular demographics has to be targeted
  • Retargeting – Targeting should be focused on historical donors, interested in your policies
  • SEO decisions – Upload content suitable for the target audience and improve search rankings
  • Email messages – it would segment your lists while enhancing campaign results

To put simply, better data yields positive results for political campaigns, along with supporting fundraising, awareness and presence. However, remember, not all data is clean and safe and not all data providers are credible and honest. Watch the news, join the drive, but stay true to your opinions and insights. They will never fail you.

Get trained by the experts from DexLab Analytics on big data hadoop. It’s a premier data analytics training institute in Delhi NCR that offers incredible big data training to the students.

The article has been sourced from:

https://www.theguardian.com/commentisfree/2017/mar/06/big-data-cambridge-analytica-democracy

https://webbula.com/how-data-helps-political-campaigns-succeed

 

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How Data Analytics Is Shaping and Developing Improved Storage Solutions

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Technology has penetrated deep into our lives – the last 5 decades of IT sector have been characterized by intense development in electronic storing solutions for recordkeeping.

 
How Data Analytics Is Shaping and Developing Improved Storage Solutions
 

Today, every file, every document is stored and archived safely and efficiently – rows of data are tabled in spreadsheets and stored in SQL relational databases for smooth access anytime by anyone, of course the authorized persons. Data is omnipresent. It is being found in data warehouses, data lakes, data mines and in pools. It is so much large in volume nowadays, that it can even be calculated in something like a Brontobyte.

 

Information is power. Data stored in archives are used to make accurate forecasts. And the data evaluation has begun within a subset of mathematics powered by a discipline named probability and statistical analysis.

 

Slowly, this discipline evolved into Business Intelligence that further into Data Science. The latter is the most sought after and well-paid career option for today’s tech-inspired generation. Grab a data science certification in Gurgaon and push your career to success.

 

Big Data Storage Challenges and Solutions

The responsibility of storage, ensuring security and provide accessibility for data is huge. Managing volumes and volumes of data is posing a challenge in itself – for example, even powering and cooling enough HDD RAID arrays to keep an Exabyte of raw data tends to break the bank for many companies.

 

Software-defined storage and flash devices are being deployed for big data storage. They promise of better direct business benefit. Also, increasingly Apache Spark Hadoop or simply Spark is taking care of the software side of big data analytics. Whether your big data cluster is developed on these open-source architectures or some other big data frameworks, it will for sure impact your storage decisions.

 

Hadoop is in this business of storage for big data for quite some time now. It is a robust open-source framework opted for suave processing of big data. It led to the emergence of server clusters and Facebook is known to have the largest Hadoop cluster containing millions of nodes.

 
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Now, the question remains where and how you proceed with Hadoop – there are so many differing opinions about how you approach Hadoop clusters, at times it may leave you exasperated. For that, we can help you here.

 

With a huge array of data at play, we suggest to deploy a dedicated processing, storage and networking system in different racks to avoid latency or performance issues. It is for the same reasons, we ask you to stay away running Hadoop in a virtual environment.

Instead, implement HDFS (Hadoop Distributed File System) – it is perfect for distributed storage and processing with the help of commodity hardware. The structure is simple, tolerant, expandable and scalable.

 

Besides, the cost of data storage should also be given a look at – cost should be kept low and data compression features should likely to be implemented.

For Big Data Hadoop certification in Delhi NCR, drop by DexLab Analytics.

 
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The Takeaway

Times are changing, and so are we. Big data analytics are becoming more real-time, hence better you scale up to real-time analytics. Today, data analytics have gone way beyond the conventional desktop considerations – it has now become a lot more, and to keep pace with the analytics evolution, you need to have sound storage infrastructure, where possible upgrades to computing, storage and networking is easily available and implementable.

 

To answer about big data or Hadoop, power yourself up with a good certification in Big Data Hadoop from DexLab Anlaytics – such intensive big data courses do help!

 

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How Big Data Will Impact E-commerce Industry in 2018?

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Whatever happens online and offline, it’s because of DATA. As the technology evolves, the ways to gather and measure data also diversifies. The best way to grasp the data world mechanisms is to study and analyze trends in behavior.

 
How Big Data Will Impact E-commerce Industry in 2018?
 

Big data is a concentrated accumulation of conventional and digital data from within and outside company operations. The inception of big data has enabled businesses to use huge amounts of data to carry out bigger and more complicated analyses.

 

However, the pressing issue that people face today is that they have “too much” data – collecting, organizing and understanding data has become quite complicated because we now are inundated with ceaseless numbers, percentages, stats, facts and perceptions.

 

To be precise, for years, Big Data has been buzzing around the digital front – let’s delve into what it actually means and what promises it holds in 2018 for ecommerce…

 

E-commerce industries are the biggest consumers of data. They can extract any information from Big Data and predict customer behavior and streamline robust operations.

Here are 4 ways in which big data will change the shape of e-commerce in 2018:

Better shopper analysis

For online success, understanding shopper’s behavior is more than important. Harness big data; it offers information on trends, customer choices and spikes in demands. It is the key to successful marketing.

 

Throughout this year and more, big data analytics will continue tracking shopper behaviors and fine-tuning your marketing strategies based on that.

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Flawless customer service

 Figures regarding dissatisfied customers and frail customer service are alarming. Truly speaking, more than 90% of unhappy customers won’t like to do business with a company that has turned their expectations down, owing to poor customer service. Therefore, for ecommerce success, utmost focus on customer service is downright important.

 

This year, expect data analytics to improve customer experience, while giving more focus to predictive monitoring. This will aid companies in identifying crucial issues and resolve them before even a customer gets involved.

More secure and easy online payment options

Since big data came into our lives, several things, like online payments got easier and more secure. How?

 

  • Big data incorporates various payment functions in a single centralized platform. It helps in making the process easier, as well as reduces fraud risks.
  • The advanced analytics are powerful enough to identify threats and structure proactive solutions to combat potent risks.
  • Big data helps in detecting money laundering transactions.
  • Productive data analytics allows e-commerce chains to cross sell and upsell.

Mobile commerce evolution

Day by day, the use of smartphones is increasing. The use of desktop computers is soon becoming obsolete. Big data is making impossible things possible, especially in the world of smartphones and ecommerce. Companies can now very easily gather data from multiple sources and analyze customer trends through mobile technology. Google has pioneered a wave of technologies, giving preference to mobile friendly and highly responsive sites. They bring in higher traffic to their pages. Hence an instant hit!

 

As closing thoughts, ecommerce companies wholeheartedly thanks Big Data for the way it has simplified the process of online shopping. For more big data inspiration and blogs, follow DexLab Analytics.

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Our advanced Big Data certification in Delhi NCR is excellent. Hone your skills with big data hadoop training and soar to success.

 
The article has been sourced from  –  http://dataconomy.com/2018/02/5-ways-big-data-analytics-will-impact-e-commerce-2018/
 

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If Big Data is the Problem, Then Hadoop is the Solution

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If Big Data is the Problem, Then Hadoop is the Solution

A lot of IT professionals and tech nerds are curious to learn about the difference between Big Data and Hadoop. A majority of them are yet to understand the subtle line of distinction between the two. And the increasing prominence and popularity of Big Data Hadoop certification has further added to the confusion.

Importantly, Big Data and Hadoop, the most popular open-source Hadoop program actually ends up complementing each other, in every way. If you think of Big Data as a problem then Hadoop acts like a solution for that problem – yes, they are that much compatible and complementary to each other. While big data is a dubious and complex concept, Hadoop being a simple, open source program that helps in fulfilling a certain creed of objectives of asset, in this case Big Data.

The best way to explain this issue would be by talking about the challenges associated with Big Data and how Hadoop efficiently resolves them – this would be the best way to know the differences between the two.

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Challenges with Big Data

Big Data is best defined with 5 characteristics: Volume, Variety, Velocity, Value and Veracity. Here, volume depicts the quantity of data, variety means the kind of data, velocity is the rate at which data is being generated, value points at the usefulness of the data and veracity is the amount of inconsistent data.

Now, let’s talk about two of the emerging problems with Big Data:

  • Storage – The archaic storage solutions are not adept enough to store such mammoth amount of data that is being generated every day. Moreover, the variety of data is different, thus the data needs to be stored separately for effective use.
  • Speed of accessing and processing data – Though the hard disk capacities have increased manifold, not much development has been done on the front of the speed of accessing or processing data.

But no more, you have to worry about all these issues, as Hadoop is here. It has effectively mitigated all the above-mentioned challenges and made big data powerful as a rock!

What is Hadoop?

Generally speaking, Hadoop is an open source programming platform – it helped big data to get stored in distributed environments so as to be processed in a parallel way. It is composed of two important elements – Hadoop Distributed File System (HDFS) and YARN (Yet Another Resource Negotiator), Hadoop’s processing unit.

Now, let’s see how Hadoop resolves the emerging big data challenges:

  • Storage – With the help of HDFS, Big Data can now be stored in a proper distributed manner. For that, datanode block is used, it’s an efficient storage solution and allows you to specify the size of every block in use. Additionally, it doesn’t only divides the data across different blocks but also replicated all the blocks on the data nodes, thus making way for better storage solution.
  • The speed of accessing and processing data – Instead of relying on traditional methodologies, Hadoop prefers moving processing to the data, which means the processing dynamo is moved across different slave nodes and parallel processing of data is carried on throughout the slave nodes. And the processed results are then shifted into a master node, where a mixing of data takes place and the response arising out of it is sent to the client.

Hence, you can see how big data and hadoop are related to each other, not like alternatives but like complements. So, to climb the ladder of success and be an ace developer or data scientist, Big Data Hadoop certification in Gurgaon is your go-to option. Get Big Data Hadoop certification today from DexLab Analytics.

 

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