Big Data Hadoop institute in Delhi Archives - Page 6 of 9 - DexLab Analytics | Big Data Hadoop SAS R Analytics Predictive Modeling & Excel VBA

Category: Big Data Hadoop institute in Delhi

10 Key Areas to Focus When Settling For an Alternative Data Vendor

Posted on by Dexlab

10 Key Areas to Focus When Settling For an Alternative Data Vendor

Unstructured data is the new talk of the town! More than 80% of the world’s data is in this form, and big wigs of financial world need to confront the challenges of administering such volumes of unstructured data through in-house data consultants.

FYI, deriving insights from unstructured data is an extremely tiresome and expensive process. Most buy-sides don’t have access to these types of data, hence big data vendors are the only resort. They are the ones who transform unstructured content into tradable market data.

Here, we’ve narrowed down 10 key areas to focus while seeking an alternative data vendor.

Structured data

Banks and hedge funds should seek alternative data vendors that can efficiently process unstructured data into 100% machine readable structured format – irrespective of data form.

Derive a fuller history

Most of the alternative data providers are new kid in the block, thus have no formidable base of storing data. This makes accurate back-testing difficult.

Data debacles

The science of alternative data is punctured with a lot of loopholes. Sometimes, the vendor fails to store data at the time of generation – and that becomes an issue. Transparency is very crucial to deal with data integrity issues so as to nudge consumers to come at informed conclusions about which part of data to use and not to use.

Context is crucial

While you look at unstructured content, like text, the NLP or natural language processing engine must be used to decode financial terminologies. As a result, vendors should create their own dictionary for industry related definitions.

Version control

Each day, technology gets better or the production processes change; hence vendors must practice version control on their processes. Otherwise, future results will be surely different from back-testing performance.

Let’s Take Your Data Dreams to the Next Level

Point-in-time sensitivity

This generally means that your analysis includes data that is downright relevant and available at particular periods of time. In other cases, there exists a higher chance for advance bias being added in your results.

Relate data to tradable securities

Most of the alternative data don’t include financial securities in its scope. The users need to figure out how to relate this information with a tradable security, such as bonds and stocks.

Innovative and competitive

AI and alternative data analytics are dramatically changing. A lot of competition between companies urges them to stay up-to-date and innovative. In order to do so, some data vendors have pooled in a dedicated team of data scientists.

Data has to be legal

It’s very important for both vendors and clients to know from where data is coming, and what exactly is its source to ensure it don’t violate any laws.

Research matters

Few vendors have very less or no research establishing the value of their data. In consequence, the vendor ends up burdening the customer to carry out early stage research from their part.

In a nutshell, alternative data in finance refer to data sets that are obtained to inject insight into the investment process. Most hedge fund managers and deft investment professionals employ these data to derive timely insights fueling investment opportunities.

Big data is a major chunk of alternative data sets. Now, if you want to arm yourself with a good big data hadoop certification in Gurgaon then walk into DexLab Analytics. They are the best analytics training institute in India.

The article has been sourced from – http://dataconomy.com/2018/03/ten-tips-for-avoiding-an-alternative-data-hangover

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.

To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

How Data Exhaust is Leveraged for Your Business

Posted on by Dexlab

How Data Exhaust is Leveraged for Your Business

Big data is the KING of corporate kingdom. Every company is somehow using this vital tech tool; even if they are not using it, they are thinking of it.

A 2017 survey says, around 53% of companies were relying on big data for their business operations. Each company focuses on a particular variant of data. Some of the data types are considered most important, while others are left out. Now what happens to the data that is kept aside?

Data exhaust can be a valuable addition for a company – if leveraged properly.

Let’s Take Your Data Dreams to the Next Level

Explaining Data Exhaust

It entirely deals with the data that is leftover but produced by the company itself. Keep in mind, when you try collect information from a specific set of data, a whole lot of information is also collected at the same time. So, many organizations might be sitting on a gold mine of data but without acknowledging the importance of that data. In instances like this, data exhaust can be very helpful across numerous business development channels.

Market Research

The best way to use data exhaust is through extensive market research. Know your audience is the key. Customers are crucial for effective marketing and product development. Nevertheless, the former involves manual research as well as analytical research, which once again leads us to analytics.

Through data exhaust, you get to know everything your customers do on your website – thus, can understand what they like better.

Cyber Security

As a potent threat, cyber crime results into potential costs to businesses all across the world. So, what role does data exhaust play? At best, it can help determine risk across different databases to develop superior cyber security plan.

Product Development

Importantly, businesses work on a plethora of projects at the same time. As a result, the issue of time crunch pops up. No one can do everything all at once, and data exhaust helps in sharpening whatever is important. Like, if your excess data says that most of your viewers visit your site through mobile device, it’s better to develop a mobile app to serve the customers better.

All Data Is Not Important

All data is not useful. Though data exhaust is useful, yet there would be times when you will come across bad data. You need to shed off those data, and get rid of data of that manner that is meaningless. Ask data experts which data to keep and which is irrelevant. Data that is of no use needs to be destroyed, because a company cannot keep trash for long.

Be Responsible for Data

Its clear data exhaust is all good and great for business, but it’s always suggestible to be cautious and responsible. There can be many legal implications, hence its suggestible to consult a data professional who have the desired know-how, otherwise things can get a bit complicated.

In this world of competitive technology, businesses have to be very careful about how they are using data to avoid any kind of negative outcomes. Be responsible and use data correctly; big data help frame a highly effective business strategy.

Looking for good big data courses? We have good news rolling your way – DexLab Analytics offers excellent big data training in Gurgaon. If interested, check out the course itinerary RN.

The blog is sourced from – http://dataconomy.com/2018/03/how-data-exhaust-can-be-leveraged-to-benefit-your-company

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.

To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

Discover: Interesting Ways Netflix Relies on Big Data

Posted on by Dexlab

Discover: Interesting Ways Netflix Relies on Big Data

Netflix boasts of over 100 million subscribers – a humongous wealth of data is stored and analyzed to enhance user experience. Big data makes Netflix the King of Stream; it keeps the customers engaged and content.

Big data recommends Netflix a list of programs that interests the viewers and this system actually influences 80% of content that is available on Netflix. Estimates say the cutting edge algorithms save $1 billion a year in value from customer retention – undoubtedly, a whopping figure for the entertainment industry.

Big data is used extensively all through Netflix application, BUT the Holy Grail is the prediction part: what the customers want to watch and enjoy matters the most. Moreover, big data is the fuel that powers up the recommendation engines that are created to serve the purpose.

netflix-and-devices-243

Healthy prediction of viewing habits

Efforts started way back in 2006, when Netflix was primarily into DVD-mailing business. It initiated the Netflix prize, rewarding $1 million to any group, which can devise the best algorithm to predict how a customer would rate a particular movie, based on previous ratings. Today, though the algorithms are constantly updated, but the principles still remain a key characteristic of a recommendation engine.

In the beginning, analysts were left with very little data about their customers, but as soon as streaming became more mainstream, new data points about their customers became easily available. What affects a particular movie had on a viewer could be assessed, as well as models were built to predict the ‘perfect storm’ situation for customers who were served with the movies they like.

Infographic-Netflix-knows-when-youre-Hooked

Identifying the next smashing series

Of late, Netflix has broadened its scope to include content creation, instead of limiting itself to being a distribution method for movie studios and other channels. This strategy is of course backed by meaningful data – which highlighted how its viewers are hungry for content directed by David Fincher and starring Kevin Spacey.

Every minute part of the production of the series is structured on data, including the colors used on the cover image of the series to draw in subscribers.

Netflix

For a quality experience

Netflix takes the quality aspect into great consideration. It closely monitors and analyzes the various factors that affect user behavior. Even, it develops models to explore how they perform. While, a large number of shows are hosted internally on its own distributed network of servers, they are also reflected around the world by ISPs and other hosts. Along with improving the user experience, efficient content streaming reduces costs for ISPs – shielding them from the cost of downloading data from Netflix server.

Big data and analytics have positioned themselves in the right order to dictate the operations across all Netflix platforms. They surely lead the pack of data by taking over distribution and production networks and re-modifying them through constant evolution and innovation of data.

Not only this, Netflix has reduced its promotional campaign budgets by targeting only the most relevant and interested people at the same time. All possible because of big data.

So, next time, when you peruse through your favorite shows in Netflix, do think and thank the power of big data. Because, big data is much more than what you think!

DexLab Analytics, a renowned big data training institute in Gurgaon is the best place to start a big data certification endeavor. The consultants are proficient in what they teach, the course curriculum is comprehensive and flexible course modules are suitable for everyone, irrespective of professionals or students.

The article has been sourced from:                                 

https://insidebigdata.com/2018/01/20/netflix-uses-big-data-drive-success

http://dataconomy.com/2018/03/infographic-how-netflix-uses-big-data-to-drive-success

https://www.linkedin.com/pulse/amazing-ways-netflix-uses-big-data-drive-success-bernard-marr

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.

To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

5 Steps to Reassess Your Big Data Business Strategy

Posted on by Dexlab

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.

2

  • 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.

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.

To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

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

Posted on by Dexlab

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.

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.
To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

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

Posted on by Dexlab

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

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.

To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

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

Posted on by Dexlab

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

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.

To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

How Big Data Plays the Key Role in Promoting Cyber Security

Posted on by Dexlab

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!

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.

To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

How Data is Found Influencing Political Campaigns Online

Posted on by Dexlab

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.

2

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

 

Interested in a career in Data Analyst?

To learn more about Data Analyst with Advanced excel course – Enrol Now.
To learn more about Data Analyst with R Course – Enrol Now.
To learn more about Big Data Course – Enrol Now.

To learn more about Machine Learning Using Python and Spark – Enrol Now.
To learn more about Data Analyst with SAS Course – Enrol Now.
To learn more about Data Analyst with Apache Spark Course – Enrol Now.
To learn more about Data Analyst with Market Risk Analytics and Modelling Course – Enrol Now.

Call us to know more

Gurgaon

+91 8676079880

Kolkata

+91 9903662244

Quick Links

Our Courses

Important dates

Copyright © 2024 DexLab Solutions Corporation | Privacy Policy | Legal Disclaimer | Terms and Conditions