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Predicting World Cup Winner 2018 with Big Data

Posted on June 21, 2018May 23, 2020 by Dexlab

Predicting World Cup Winner 2018 with Big Data

Is there any way to predict who will win World Cup 2018?

Could big data be used to decipher the internal mechanisms of this beautiful game?

How to collect meaningful insights about a team before supporting one?

Data Points

Opta Sports and STATS help predict which teams will perform better. These are the two sports companies that have answers to all the above questions. Their objective is to collect data and interpret it for their clients, mainly sports teams, federations and of course media, always hungry for data insights.

How do they do it? Opta’s marketing manager Peter Deeley shares that for each football match, his company representatives collects as many as 2000 individual data points, mostly focused on ‘on-ball’ actions. Generally, a team of three analysts operates from the company’s data hub in Leeds; they record everything happening on the pitch and analyze the positions on the field where each interaction takes place. The clients receive live data; that’s the reason why Gary Lineker, former England player is able to share information like possession and shots on goal during half time.

The same procedure is followed at Stats.com; Paul Power, a data scientist from Stats.com explains how they don’t rely only on humans for data collection, but on latest computer vision technologies. Though computer vision can be used to log different sorts of data, yet it can never replace human beings altogether. “People are still best because of nuances that computers are not going to be able to understand,” adds Paul.

Who is going to win?

In this section, we’re going to hit the most important question of this season – which team is going to win this time? As far as STATS is concerned, it’s not too eager to publish its predictions this year. The reason being they believe is a very valuable piece of information and by spilling the beans they don’t want to upset their clients.

On the other hand, we do have a prediction from Opta. According to them, veteran World Cup champion Brazil holds the highest chance of taking home the trophy – giving them a 14.2% winning chance. What’s more, Opta also has a soft corner for Germany – thus giving them an 11.4% chance of bringing back the cup once again.

If it’s about prediction and accuracy, we can’t help but mention EA Sports. For the last 3 World Cups, it maintained a track record of predicting the eventual World Cup winner impeccably. Using the encompassing data about the players and team rankings in FIFA 2018, the company representatives ran a simulation of the tournament, in which France came out to be the winner, defeating Germany in the final. As it has already predicted right about Germany and Spain in 2014 and 2010 World Cups, consecutively, this new revelation is a good catch.

So, can big data predict the World Cup winner? We guess yes, somehow.

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The blog has been sourced from – https://www.techradar.com/news/world-cup-2018-predictions-with-big-data-who-is-going-to-win-what-and-when

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Transformation On-The-Go: See How Financial and Manufacturing Sectors are Harnessing Big Data Hadoop

Posted on June 19, 2018May 23, 2020 by Dexlab

big data hadoop course

An elderly man of 50 years of age was on the treadmill, when suddenly he received an alert on his Apple Watch showing his pulse has shot up abnormally high, putting him at the risk of a possible heart attack. Immediately he got off from the treadmill and his life was saved!

Thanks to Pontem, an incredible platform that intakes input from Apple Watch and Fitbit and issues such consequential alerts wielding machine learning, cloud-based data and cognitive processing. From the point of view of a user, these alerts are life-saver, but for the developers, it implies the latest evolution of big data technology, especially Hadoop ecosystem. Once a mere data managing tool, Hadoop is maturing and making its way to the next level.

Today, Hadoop is the lifeblood of industry-specific solutions. But adopting it for your business is no mean feat. You need to have a specific approach in sync with the particular industry type.

Financial Sector & Manufacturing

After healthcare, financial and manufacturing industry is the biggest consumer of Hadoop technology. Besides, managing, storing and analyzing data, big data coupled with AI and machine learning helps understand the intricacies of credit risk more effectively.

Of late, credit risk management has been troubling financial services companies. Though the entire banking industry has matured, the constantly evolving nature of models has been a headache for traditional credit risk models. However, the expansiveness of big data and availability in multiple formats has helped companies ace in advanced credit risk models – which was next to impossible even a few years back.

With Big Data Hadoop, a large amount of customer data is available – including online browsing activity, user spending behavior and payment options, all of which helps banks and other financial institutions frame better decisions. Commendable Hadoop’s ability to manage and manipulate unstructured data is put to use for respective functions. Over the years, Hadoop has evolved to offer sound flexibility and massive scalability to manage big data. Incorporating AI and Machine Learning, the new sophisticated models based on Hadoop clusters breaks down big data into small, easy-to-comprehend chunks, while adapting to changing, innovative data patterns. In short, the management of big data has now become comparatively an easy task – using low cost hardware, self healing, self learning and internal fault tolerance attributes. No more, you feel like stuck in a cleft stick, while handling such a massive infrastructure of big data.

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For manufacturing industry, predictive analytics is the key that’s bringing in large-scale digital transformation – internet connections and sensors are providing real-time data for better operations. Sensors have the ability to detect prior anomalies in the production process, thereby preventing production of defective items and curtail subsequent waste. Often, there is a deep learning or AI connect to the analytics layers existing on the top of Hadoop data lakes that offers suave data analytics and self-learning capabilities. It’s said, around 80% of manufacturers will implement cutting edge technology in the next few years. And the numbers are just increasing.

Hadoop is not like a magic potion. It’s a robust platform on which you can harness the data power. However, to master Hadoop technology, you need to have required knowledge and expertise as per the industry standards. DexLab Analytics is a well-recognized Big Data Hadoop institute in Noida. They offer an extensive range of courses on in-demand skills, including Big Data Hadoop training in Delhi.

Check out their latest admission drive #BigDataIngestion: students can avail 10%off on in-demand courses, like big data hadoop, data science, machine learning and business analytics. Limited offer. Hurry!

This blog has been sourced from: http://dataconomy.com/2018/05/hadoop-evolved-how-industries-are-being-transformed-by-big-data/

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How Big Data is Revolutionizing Political Campaigns in America

Posted on June 8, 2018 by Dexlab

How Big Data is Revolutionizing Political Campaigns in America

No doubt that big data is altering the manner in which politicians win elections in America, but it is also breaking American politics. So was the verdict in a column by NBC’s Chuck Todd and Carrie Dann.

According to Todd and Dann, recent technological advancements give access to detailed voter information and demographic data, like what they watch, what they shop and what they read; campaign initiators are completely aware of the preferences of voters. Hence, it enables them to target people who are most likely to vote for them through ads and other relevant content. They don’t feel the need to persuade the ones who are less likely to agree with their ideologies. Clearly, this is a crisis situation that fuels polarization within a governing system. It is encouraging campaigns to appeal to their most likely supporters rather than all their constituents. Also, this process is cheaper and faster.

Eitan Hersh, a notable professor of political science at Yale University conducted research on the role of big data and modern technology in mobilizing voters. So, let’s find out if his research work indicates the situation to be as adverse as Todd and Dann claims it to be.

New sources of data:

Earlier, campaigns relied on surveys to generate their data sets, which were based on a sample of the entire population. Now campaigns can use data that is based on the entire population. The data sets that are looked into include voter registration data, plenty of public datasets and consumer databases. Zonal data, like neighborhood income, can be accessed via the Census Bureau. Information about a voter, like her party affiliation, gender, age, race and voting history is often listed in public records. For example, if a democratic campaign is aware that a person has voted for a Democratic party previously, is Latino or of African origin and is under 25 years, then it is highly probable that this person will vote for them.

Once campaigns chalk out their team of supporters, they employ party workers and tools like mails and advertisements to secure their votes.

Hacking the electorate:

According to Eitan Hersh, it is truly impossible to completely understand the interests of the entire population of voters. However, campaigns are focusing heavily on gathering as much data as possible. The process consists of discovering new ways existing data can be utilized to manipulate voters; asking the right questions; predicting the likeliness of a group to vote for a particular candidate, etc. They need to find sophisticated ways to carry out these plans. The ever increasing volume of data is definitely aiding these processes. Campaigns can now customize their targeting based on individual behavior instead of the behavior of a standard constituent.

Types of targeting:

There are chiefly 4 methods of targeting, which are not only used for presidential elections but also for targeting in local elections. These are:

Geographic targeting: This helps target people of a particular zip code, town or city and prevents wastage of money, as ads are focused on people belonging to a specific voting area.
Demographic targeting: This helps targeting ads to specific groups of people, such as professionals working in blue-chip companies, men within ages 45 and 60 and workers whose salaries are within $60k per year for example.
Targeting based on interest: For example, ads can be targeted to people interested in outdoor sports or conservation activities.
Targeting based on behavior: This is basically the process in which past behavior and actions are analyzed and ads are structured based on that. Retargeting is an example of behavioral targeting where ads are targeted to those who have interacted with similar posts in the past.

To conclude, it can be said that victory in politics involves a lot more than using the power of big data to reduce voters to ones (likely voters) and zeros (unlikely voters). Trump’s victory and Clinton’s defeat is an example of this. Although, Clinton targeted voters through sophisticated data-driven campaigns, they might have overlooked hefty vote banks in rural areas.

To read more interesting blogs on big data and its applications, follow Dexlab Analytics – we provide top-quality big data Hadoop certification in Gurgaon. To know more, take a look at our big data Hadoop courses.

References:

https://www.vox.com/conversations/2017/3/16/14935336/big-data-politics-donald-trump-2016-elections-polarization

https://www.entrepreneur.com/article/309356

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

Posted on May 8, 2018May 23, 2020 by Dexlab

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.

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

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How Data Exhaust is Leveraged for Your Business

Posted on May 4, 2018May 4, 2018 by Dexlab

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.

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.

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

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Discover: Interesting Ways Netflix Relies on Big Data

Posted on May 3, 2018May 23, 2020 by Dexlab

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.

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.

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.

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

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Evolving Logistics Scenario: The Tech-driven Future of Logistics Industry

Posted on April 27, 2018April 5, 2019 by Dexlab

Customer expectations are growing by the day; they are demanding faster and more flexible deliveries at minimum delivery costs. Businesses are being pressurized to customize their manufacturing processes as per customer demands. This is a hard slog for the logistics industry, which has to keep delivering better services but for lower prices.

The logistics industry can only achieve this through ‘digital fitness’. It has to make intelligent use of the global wave of digitization, including data analytics, automation and ‘Physical Internet’. The Physical Internet is an open global logistics system that is transforming the way physical objects are handled, moved, stored and supplied. It aims towards the replacement of current logistical models and making global logistics more efficient and sustainable. The Physical Internet promises better standardization in logistics operations, including shipment sizes, labeling and systems.

The central theme in logistics sector is collaborative working, which enables market leaders to retain dominance.

Now, let us take a look at a few tech-driven domains that will shape the future of logistics.

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The future of Logistics Lies in IoT

Internet of Things has been the most innovative technology of the present era. It has the potential to revolutionize the logistics sector. The key benefits of IoT with regard to logistics are:

Real-time alerts and notifications
Automate processes that gather data from various machines
Automate vital operations like inventory management and asset tracking: With the help of IoT, companies can improve tasks like tracking orders, determining what items need to be stocked up and how certain products are performing.
Able to function without any human interventions.
Logistic companies can provide safer deliveries
Enable the regulation of temperature and other environmental factors.

IoT will be advantageous for the entire logistics sector, including fleet and warehouse management, and shipment and delivery of products. IoT can help companies dealing with cargo shipments by improving visibility in the delivery and tracking of cargo.

Warehouse Automation

Warehouse automation is set for a major overhaul. Online shopping is thriving and logistics, especially warehouse operations, need to be more refined and speedy. Warehouse operations of many e-commerce giants are undergoing a robotics makeover. According to reports, the market for logistics robotics, which had generated revenues worth 1.9 billion USD in 2016, is likely to generate sky-high revenues worth 22.4 billion USD this year.

The advancements in robotics include programming robots to pick and pack goods, load and unload cargo and at times deliver goods too. Employing robots speed up the processes of data collection, maintaining records and managing inventories. Most importantly, robots leave no room for human errors in the processes.

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Blockchain Technology in Logistics

The growth of crypto-currencies like Bitcoin has popularized blockchain technology. Blockchain being a type of distributed ledger technology provides secure, traceable and transparent transactions. Blockchain technology employed by logistics firms will improve customer visibility into shipments and help prevent data breaches.

In the present times, logistics is considered the backbone of a stable economy. Thus, for India to emerge as a superpower, the logistics market needs to be developed and integrated with state-of-the-art technologies. Conducive policies and a healthy partnership between private and public sector is crucial to steer India into an era of competent and cost-effective business operations.

In times to come, automation will transform every industry. Don’t be left behind. Get an edge by enrolling for the data science and machine learning certification course at the premier data analyst training institute in Delhi– Dexlab Analytics.

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

Posted on April 13, 2018May 23, 2020 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.

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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How Big Data Plays the Key Role in Promoting Cyber Security

Posted on April 6, 2018May 23, 2020 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.

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.

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.

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.

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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