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R Vs Python: A Debate Forever

Posted on October 30, 2019 by Dexlab

R Vs Python: A Debate Forever

In this blog, we will bring forth the age old question and check which one is better, R programming and Python programming, when it comes to data science?

To be very honest, this question does not have a strict answer to it. However, in this blog we will lay down the key components of both the languages to give you a clearer picture. In the end, please decide for yourself and leave your comments in the section below.

The aim of this blog is to objectively put forward the pros and cons of both languages strictly from the perspective of data science.

We will discuss only about three main components, which are as follows:

Syntax
Performance
Applicability

There are other metrics, such as, trends in Industries and adaptation in the recent years which are beyond the scope of this blog. However, you can safely declare Python as the clear winner if those perspectives were concerned.

So let’s get started:

Syntax

Both R and Python are object-oriented languages. This is to say that everything is created as an object in which the information is mapped with the idea of using that object later in the analysis. However, when it comes to the syntax, i.e., the grammar of programming, R and Python are indeed very different.

R Programming

R programing is more suited to more seasoned coders who have prior experience of coding. The syntax is actually very similar to that of the previous languages, such as C, or C++ or Java and so on. The fundamental rules are that of C programming language. Also, use of semicolons is deemed optional in R. However, semicolons are necessary for multiple lines in a code inside a code block.

Python

Python on the other hand, is the language more adaptable to the new generation of programmers. You can come from a non-programming background and still learn Python with relative ease.

Python is one of the most user friendly languages for the beginners. The syntax is designed to prioritize readability over preciseness of the code. In layman’s terms – coding in Python is very close to reading and writing with hand. In this regard, it is really popular amongst beginners in Data Science.

Performance

The performance is essentially measured by speed essentially when it comes to programming.

R Programming

As far as the general consensus goes R programming is much slower in terms of speed. The reason behind this is that R programming was initially designed to be used by statisticians for data analysis. Thus, R programming stresses more on precision than the speed.

Python

Python on the other hand, is relatively faster than R. Python offers the same level of precision whilst acting on a faster speed.

Note – The speed is taken into account independent of packages and libraries.

Applicability

Lastly, we will discuss the popular domains in which these languages are used.

R Programming

As mentioned above, R was developed specifically for statisticians. For this reason, R is mainly used in various research organizations and academia in general. However, R is now quickly being absorbed in the enterprises as well, mainly because of its popularity and the availability of a large number of packages for statistical computation.

Python

Python is a gene

As Python is a general-purpose programming language we can use to build different kinds of applications. We can use Python to build web applications using popular frameworks like Django or Flask.

Lately, Python is becoming popular amongst data scientists as the language of choice given the simplicity of syntax, high speed and performance it has to offer. There has been a trend which has seen a sharp rise in the adaptability of Python over R in the last few years in Data Science.

So, there you have it folks. Decide for yourself now! We will meet you soon in the next blog.

Dexlab Analytics is a pioneering institute of Data Science and Big Data Analytics with all-inclusive Big data courses in Delhi along with numerous other efficacious courses like Hadoop certification in Delhi, R programming courses in Gurgaon and Python for Data Analysis under experienced trainers and professionals.

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The Impact of Big Data on the Legal Industry

Posted on April 9, 2019April 13, 2019 by Dexlab

The Impact of Big Data on the Legal Industry

The importance of big data is soaring. Each day, the profound impact of data analytics can be felt across myriad domains of digital services – courtesy an endless stream of information they generate. Yet, a handful number of people actually ponders over how big data is influencing society’s some of the most important professions, including legal. In this blog, we are going to dig into how big data is impacting the legal profession and transforming the dreary judiciary landscape across the globe.

Importance of Big Data

Information is challenging our legal frameworks. Though technology has transformed lives 360-degree, most of the country’s bigwigs and institutions are still clueless about how to harness the power of big data technology and reap significant benefits. The men in power remain baffled about the role of data. The information age is frantic and the recent court cases highlight that the Supreme Court is facing a tough time taming the big data.

However, on a positive note, they have identified the reason of slowdown and are joining the bandwagon to upgrade their digital skills and upend tech modernization strategies. Data analytics is a growing area of relevance and it must be leveraged by the nation’s biggest legal authorities and departments. From tracking employee behaviors to scanning through case histories, big data is being employed everywhere. In fact, criminal defense lawyers are of the opinion that big data is altering their courtroom approaches, which have always dominated the trials with a set of certain evidence. Today, the pieces of evidences have become digital than judicial.

Boon for Law Enforcement Officials

The technology of big data has proved to be a welcoming-change for the army of law enforcement officials; the reason being efficiency in prosecuting a large number of criminals in a jiffy. Officials can now scan through piles and piles of data at a super-fast pace and handpick scam artists, hackers and delinquents. Besides law enforcers, police officers are also identifying threats and rounding up criminals before they even plan to get way.

Moreover, the prosecutors are leveraging droves of data to summon up evidence to support their legal arguments in court. That’s helping them win cases! For example, of late, federal prosecutors served a warrant to Microsoft to gain access to their data pool. It was essential for their case.

Big Data Transforming Legal Research

Biggest of all, big data is transforming the intricacies of the legal profession by altering the ways how scholars research and analyze the court proceedings. For example, big data is used to study the Supreme Court’s arguments and we have discovered that arguments are becoming more and more peculiar in their own ways.

Such research tactics will largely lead the show as big data technology tends to become cheaper and more widely popular across the market. In the near future, big data is going to be applied in a plethora of industry verticals and we are quite excited to witness impactful results.

As a matter of fact, you don’t have to wait long to see how big data changes the legal landscape. In this flourishing age of round-the-clock information exchange, the change will take no time.

Now, if you are interested in Big Data Hadoop certification in Delhi, we’ve good news rolling your way. DexLab Analytics provides state-of-the-art big data courses – crafted by industry experts. For more, reach us at <www.dexlabanalytics.com>

The blog has been sourced from — e27.co/how-big-data-is-impacting-the-legal-world-20190408

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Big Data Analytics for Event Processing

Posted on March 26, 2019March 26, 2019 by Dexlab

Courtesy cloud and Internet of Things, big data is gaining prominence and recognition worldwide. Large chunks of data are being stored in robust platforms such as Hadoop. As a result, much-hyped data frameworks are clouted with ML-powered technologies to discover interesting patterns from the given datasets.

Defining Event Processing

In simple terms, event processing is a typical practice of tracking and analyzing a steady stream of data about events to derive relevant insights about the events taking place real time in the real world. However, the process is not as easy as it sounds; transforming the insights and patterns quickly into meaningful actions while hatching operational market data in real time is no mean feat. The whole process is known as ‘fast data approach’ and it works by embedding patterns, which are panned out from previous data analysis into the future transactions that take place real time.

Employing Analytics and ML Models

In some instances, it is crucial to analyze data that is still in motion. For that, the predictions must be proactive and must be determined in real-time. Random forests, logistic regression, k-means clustering and linear regression are some of the most common machine learning techniques used for prediction needs. Below, we’ve enlisted the analytical purposes for which the organizations are levering the power of predictive analytics:

Developing the Model – The companies ask the data scientists to construct a comprehensive predictive model and in the process can use different types of ML algorithms along with different approaches to fulfill the purpose.

Validating the Model – It is important to validate a model to check if it is working in the desired manner. At times, coordinating with new data inputs can give a tough time to the data scientists. After validation, the model has to further meet the improvement standards to deploy real-time event processing.

Top 4 Frameworks for ML in Event Processing

Apache Spark

Ideal for batch and streaming data, Apache Spark is an open-source parallel processing framework. It is simple, easy to use and is ideal for machine learning as it supports cluster-computing framework.

Hadoop

If you are looking for an open-source batch processing framework then Hadoop is the best you can get. It not only supports distributed processing of large scale data sets across different clusters of computers with a single programming model but also boasts of an incredibly versatile library.

Apache Storm

Apache Storm is a cutting edge open source, big data processing framework that supports real-time as well as distributed stream processing. It makes it fairly easy to steadily process unbounded streams of data working on real-time.

IBM Infosphere Streams

IBM Infosphere Streams is a highly-functional platform that facilitates the development and execution of applications that channels information in data streams. It also boosts the process of data analysis and improves the overall speed of business decision-making and insight drawing.

If you are interested in reading more such blogs, you must follow us at DexLab Analytics. We are the most reputed big data training center in Delhi NCR. In case, if you have any query regarding big data or Machine Learning using Python, feel free to reach us anytime.

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Transforming Construction Industry With Big Data Analytics

Posted on March 19, 2019April 16, 2019 by Dexlab

Transforming Construction Industry With Big Data Analytics

Big Data is reaping benefits in the construction industry, especially across four domains – decision-making, risk reduction, budgeting and tracking and management. Interestingly, construction projects involve a lot of data. Prior to big data, the data was mostly siloed, unstructured and gathered on paper.

However, today, the companies are better equipped to utilize the power of big data and employ it in a better way. They can now easily capture data with the help of numerous high-end devices and transform the processes. In a nutshell, the result of implementing big data analytics is positive and everybody involved is enjoying the benefits – namely improved decision-making, higher productivity, better jobsite safety and minimum risks.

Moreover, using the previous data, construction companies now can predict future outcomes and focus on projects that are expected to be successful. All this makes big data the most trending tool of the construction industry and for all the right reasons. The sole challenge is, however, how businesses adopt these robust changes.

Reduce Costs via Optimization

To stay relevant and maintain a competitive edge, continuous optimization of numerous processes is important. Big data lends a helping hand to ensure the efficacy of such processes by keeping a track of all the processes from first to the very last step – making them quick and productive. With big data technology, companies can easily understand the areas where improvements are required and devise the best strategy.

Needless to say, the primary focus of optimization is to reduce costs and unnecessary downtime. Big Data is by far tackling this concern well.

Worker’s Productivity is Important

Generally, when we discuss productivity in the construction industry, it mostly concerns technology and machines – leaving behind a crucial factor, humans. Big data takes into account each worker’s productivity. It is no big deal to track their work progress. In fact, it will help increase their productivity and boost efficiency.

Furthermore, when a lot of data is at hand, companies can even analyze how their workers are interacting to discover ways to enhance their efficiency levels by replacing tools and technologies.

The Role of Data Sharing

The construction industry is brimming with data. There is so much data here that it needs another capable organization to handle such vast piles of information. Among other things, companies need to share information with their stakeholders. They also need to strategize this data for better accessibility.

Ultimately, the main task of these companies is to eliminate data silos if they really want to savor the potentials of this powerful technology to the fullest. Till date, they have been successful.

In a nutshell, we can say that big data is positively impacting the whole construction industry and is more likely to expand its horizons in the next few years. However, the companies need to learn how to imbibe this cutting edge technology to enjoy its enormous benefits and sail towards the tides of success – because big data is here to stay for long!

DexLab Analytics is a phenomenal Big Data Hadoop institute in Delhi NCR that is well-known for its in-demand skill training courses. If you are thinking of getting your hands on Hadoop certification in Delhi, this is the place to go. For more details, drop by our website.

The blog has been sourced from — www.analyticsinsight.net/how-big-data-is-changing-construction-industry

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DexLab Analytics is Providing Intensive Demo Sessions in March

Posted on March 14, 2019March 14, 2019 by Dexlab

DexLab Analytics is Providing Intensive Demo Sessions in March

The internet has spurred quite a revolution – in several sectors, including education. Interested candidates are at liberty today to learn a vast array of things and garner a humongous pool of knowledge. Online demo sessions further add to the effect. These demo sessions are state-of-the-art and in sync with the industry demands. They are one of the most effective methods of learning and upgrading skills, particularly for the professionals. They transform the learning process and for all the good reasons.

DexLab Analytics is a premier data science training institute that conducts demo sessions, online and offline regularly. These demo sessions are indeed helpful for the students. With an encompassing curriculum, a team of experts and a flexible timing, the realm of demo sessions has become quite interesting and information-laden.

Talking of online sessions, they are incredibly on-point and high on flexibility. With daring innovations in technology, no longer do you have to travel for hours to reach your tuition center. Instead, from the confines of your home sweet home, you can gain access to these intensive demo sessions and learn yourselves. Adding to that, the medium of learning is easy and user-friendly. The millennial generation is extremely tech-savvy that leaves no room for difficulties learning online.

Moreover, we boast of top-of-the-line faculty strength, well-versed in the art and science of data science and machine learning. With years of experience and expertise, the consultants working with us are extremely professional and knowledgeable in their respected field of study. Lastly, online demo sessions are great tools for career advancement. While working, you can easily upgrade your skills in your own time – boosting career endeavors further. The flexibility of learning is the greatest advantage.

This month, DexLab Analytics is organizing the following demo sessions; kindly take a note of the date and timing:

Demo session on Machine Learning, Deep Learning and Python – Saturday 16th March at 2 PM by industry professionals
Demo session on Data Visualization and Reporting – Saturday 23rd March at 11 AM by industry professionals
Demo session on Credit Risk Modelling – Saturday 16th March at 2 PM by industry professionals

For more information on big data Hadoop training in Delhi, follow DexLab Analytics.

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Enhancing Food Safety with IoT and Big Data Analytics: Here’s how

Posted on March 1, 2019March 1, 2019 by Dexlab

Enhancing Food Safety with IoT and Big Data Analytics: Here’s how

We’ve all gone through it – sudden publicity regarding a particular food item being ‘’unsafe and hazardous’’ that sends us rummaging through our kitchen to discard those products. But in this age where everything goes through multiple inspections, how do these errors happen?

The truth is tracking the source of contaminated food and isolating compromised items isn’t all that efficient. This is where big data analytics and IoT can play game-changing roles. These two revolutionary techs have disrupted many industries for good, and promise to positively transform the food sector too.

IoT for Tracing Shipments

IoT in the form of RFID tags and barcodes are popularly used in the food industry to track shipped food products from source till destination, ensuring retailers acquire the ordered products safely and fulfill consumer demand. However, recently advanced IoT sensors are being used to obtain more detailed information about food products being transported all over the world. These sensors can greatly enhance food safety – they have the capability of identifying minute dust particles and keeping track of environmental conditions like temperature. For example, these sensors can be used for monitoring temperature of frozen chicken being shipped between China and U.S., as above-freezing temperatures will jeopardize their safety. Some sensors even relay data in real-time, making sure optimal conditions affirmed by safety guidelines are always maintained.

IoT Helping Investigations

Human investigators aren’t always capable of detecting the source of contamination following the discovery of fouled food items. It isn’t humanly possible to locate all the touch points in our modern and highly complex food processes. But IoT technology, with its superior tracking and supervising capabilities, can assist these investigations by spotting the exact point where the contamination occurred.

Addition of Big Data

A side benefit of IoT is the addition of a great deal of data that lay unused in cyberspace. Once all this data is assembled and analyzed, it will help track failure points, identify patterns in food-safety failures and even predict the conditions that cause food spoilage in future.

Assistance for Cultivators

Using big data related to weather and analyzing historical patterns, many tech companies are recognizing potential natural disasters beforehand. This can hugely benefit crop producers. For example, certain environmental conditions can boost the growth of unwanted pests that makes the produce unsafe for consumption. This information can help take necessary preventive measures.

Genetic Indexing

With the help of big data, correlation between bacteria RNA and DNA can be identified, resulting in genetic indexing for particular foods. Firstly, with the help of this information, food inspectors can spot harmful bacteria in food items. After this, IoT can be employed to track down the source. Once the starting point has been identified, more data can be obtained from there about the conditions that foster bacterial growth, allowing such circumstances to be avoided in future.

Improving Storage Safety with IoT and Big Data

Infestation with rats and other unwanted animals is a common problem in food storage facilities. But real-time data coming from IoT sensors combined with historical data on infestations now enables storage units to improve their conditions and protect the environment from such infestations.

Together IoT and Big Data can Promote Better Collaboration

According to WHO estimates, food-borne illnesses affect approximately 600 million people worldwide, out of them around 420,000 people pass away. To improve this condition, everyone working in the food industry must work collaboratively. And the ability of access big data and take help of an advanced technology like IoT will greatly assist this collaboration.

Every industry is going through an overhaul because of big data. In today’s world, big data education offers great power to all professionals. That’s why you must consider the top-grade big data courses in Delhi. Practical-based courses are delivered by industry experts and each student is given individual attention based on his/her level – this is what makes DexLab Analytics a leading Big Data Hadoop institute in Delhi NCR.

Reference: www.forbes.com/sites/andrewarnold/2019/02/20/how-iot-and-big-data-analytics-can-make-our-food-safer/#785e1d3d1d45

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Big Data and Its Influence on Netflix

Posted on March 1, 2019March 1, 2019 by Dexlab

Big Data and Its Influence on Netflix

With resonating hits, like Bird Box and Bandersnatch, Netflix is revolutionizing the entertainment industry – all with the power of big data and predictive analytics.

Big Data Analytics is the heart and soul of Netflix, says the Wall Street Journal. Not only the company relies on big data to optimize its video streaming quality but also to tap into customer entertainment preferences and content viewing pattern. This eventually helps Netflix target its subscribers with content and offers on shows they prefer watching.

Committed to Data, Particularly User Data

With nearly 130 million subscribers, Netflix needs to collect, manage and analyze colossal amounts of data – all for the sole purpose of enhancing user experience. Since its inception days of being a mere DVD distributor, Netflix has always been obsessed about user data. Even then, the company had an adequate reservoir of user data and a robust recommendation system. However, it was only after the launch of its incredible streaming service that Netflix took the game of data analytics to an altogether different level.

In fact, Netflix invested $1 million in a cutting-edge developer company for coming up with an algorithm that increased the accuracy of their already-existing recommendation engine by almost 10%. For this, Netflix can now save $1 billion annually from customer retention.

Netflix Already Knows What You Going to Watch Next

Yes, Netflix is a powerhouse of user behavior information. The content streaming giant knows your viewing habits better than you – courtesy pure statistics, preferably predictive analytics. This is one of the major strengths of Netflix – the way it analyzes data, adjusts algorithms and optimizes video streaming experience is simply incredible.

However, nothing great comes easy. Close monitoring of user viewing habits is essential. Right from how much time each user spends on picking movies to the number of times he/she watches a particular show, each and every data is extremely important. Moreover, conventional calculus helps Netflix in understanding its user behavior trends and necessarily provides them with appropriate customized content.

As closing thoughts, Netflix is a clear-cut answer to how technological advancement has influenced human creativity beyond levels. Powered by big data and predictive analytics, Netflix has surely debunked several lame theories on content preference and customer viewing habits. So, if you are interested in big data Hadoop training in Delhi, this is the time to act upon. With DexLab Analytics by your side, you can definitely give wings to your dreams, specifically data dreams.

The blog has been sourced from — www.muvi.com/blogs/deciphering-the-unstoppable-netflix-and-the-role-of-big-data.html

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Big Data Enhances Remote IT Support: Here’s How

Posted on February 21, 2019May 23, 2020 by Dexlab

Big Data Enhances Remote IT Support: Here’s How

Big data is the backbone of modern businesses. All their decisions are data driven. Firstly, information is aggregated from various sources, like customer viewing pattern and purchasing behavior. After this, the data is analyzed and then actionable insights are generated. Nowadays, most companies rely on some type of business intelligence tool. All in all, information collection is increasing exponentially.

However, in many cases the desire for information has gone too far. The recent scandal involving Facebook and Cambridge Analytica stands as an example. It has left people very insecure about their online activities. Fears regarding violation of privacy are rising; people are worried that their data is being monitored constantly and even used without their awareness. Naturally, everyone is pushing for improved data protection. And we’re seeing the results too – General Data Protection Regulation (GDPR) in EU and the toughening of US Data Regulations is only the beginning.

Although data organization and compliance have always been the foundation of IT’s sphere of activity, still businesses are lagging behind in utilizing big data in remote IT support. They have started using big data to enhance their services only very recently.

Advantages of data-directed remote IT support

The IT landscape has undergone a drastic change owing to the rapid advancement of technology. The rate at which devices and software packages are multiplying, Desktop Management is turning out to be a nightmarish task. Big data can help IT departments manage this situation better.

Managing complexity and IT compliance

The key reasons behind maximum number of data breaches are user errors and missing patches. Big data is very useful in verifying if endpoints are on conformity with IT policies, which in turn can help prevent such vulnerabilities and keep a check on networks.

Troubleshooting and minimizing time-to-resolution

Data can be utilized to develop a holistic picture of network endpoints, ensuring the helpdesk process is more competent. By offering deeper insight into networks, big data allows technicians to locate root causes behind ongoing issues instead of focusing on recurring symptoms. The direct effect of this is an increase in first-call-resolution. It also helps technicians to better diagnose user problems.

Better end-user experience

Having in-depth knowledge about all the devices of a network means that technicians don’t have to control an end-user’s system to solve the issue. Also, this enables the user to continue working uninterrupted while the technician takes care of the problem from behind-the-scene. Thus, IT can offer a remedy even before the user recognizes there’s a problem. For example, a team engaged in collection of network data may notice that few devices need to be updated, which they can perform remotely.

Better personalization without damaging control

IT teams have always found it difficult to manage provisioning models, like BYOD (bring your own device) and COPE (corporate owned, personally enabled). But with the help of big data, IT teams can divide end users based on their job roles and also support the various provisioning models without compromising with control. Moreover, they constantly receive feedback, allowing them keep to a check on any form of abuse, unwanted activities and any changes in the configuration of a system.

Concluding:

In short, the organization as a whole benefits from data-directed remote support. IT departments can improve on their delivery service as well as enhance end-user experience. It gives users more flexibility, but doesn’t hamper security of IT teams. Hence, in this age of digital revolution, data-driven remote support can be a powerful weapon to improve a company’s performance.

Knowing how to handle big data is the key to success in all fields of work. That being said, candidates seeking excellent Big Data Hadoop training in Gurgaon should get in touch with DexLab Analytics right away! This big data training center in Delhi NCR offer courses with comprehensive syllabus focused on practical training and delivered by professionals with excellent domain experience.

Reference: https://channels.theinnovationenterprise.com/articles/how-big-data-is-improving-remote-it-support

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Big Data and Its Use in the Supply Chain

Posted on February 18, 2019May 23, 2020 by Dexlab

Big Data and Its Use in the Supply Chain

Data is indispensable, especially for modern business houses. Every day, more and more businesses are embracing digital technology and producing massive piles of data within their supply chain networks. But of course, data without the proper tools is useless; the emergence of big data revolution has made it essential for business honchos to invest in robust technologies that facilitate big data analytics, and for good reasons.

Quality Vs Quantity

The overwhelming volumes of data exceed the ability to analyze that data in a majority of organizations. This is why many supply chains find it difficult to gather and make sense of the voluptuous amount of information available across multiple sources, processes and siloed systems. As a result, they struggle with reduced visibility into the processes and enhanced exposure to cost disruptions and risk.

To tackle such a situation, supply chains need to adopt comprehensive advanced analytics, employing cognitive technologies, which ensure improved visibility throughout their enterprises. An initiative like this will win these enterprises a competitive edge over those who don’t.

Predictive Analytics

A striking combination of AI, location intelligence and machine learning is wreaking havoc in the data analytics industry. It is helping organizations collect, store and analyze huge volumes of data and run cutting edge analytics programs. One of the finest examples is found in drone imagery across seagrass sites.

Thanks to predictive analytics and spatial analysis, professionals can now realize their expected revenue goals and costs from a retail location that is yet to come up. Subject to their business objectives, consultants can even observe and compare numerous potential retail sites, decrypting their expected sales and ascertain the best possible location. Also, location intelligence helps evaluate data, regarding demographics, proximity to other identical stores, traffic patterns and more, and determine the best location of the new proposed site.

The Future of Supply Chain

Talking from a logistic point of view, AI tools are phenomenal – IoT sensors are being ingested with raw data with their aid and then these sensors are combined with location intelligence to formulate new types of services that actually help meet increasing customer demands and expectations. To prove this, we have a whip-smart AI program, which can easily pinpoint the impassable roads by using hundreds and thousands of GPS points traceable from an organization’s pool of delivery vans. As soon as this data is updated, route planners along with the drivers can definitely avoid the immoderate missteps leading to better efficiency and performance of the company.

Moreover, many logistics companies are today better equipped to develop interesting 3D Models highlighting their assets and operations to run better simulations and carry a 360-degree analysis. These kinds of models are of high importance in the domain of supply chains. After all, it is here that you have to deal with the intricate interplay of processes and assets.

Conclusion

Since the advent of digital transformation, organizations face the growing urge to derive even more from their big data. As a result, they end up investing more on advanced analytics, local intelligence and AI across several supply chain verticals. They make such strategic investments to deliver efficient service across the supply chains, triggering higher productivity and better customer experience.

With a big data training center in Delhi NCR, DexLab Analytics is a premier institution specializing in in-demand skill training courses. Their industry-relevant big data courses are perfect for data enthusiasts.

The blog has been sourced from ― www.forbes.com/sites/yasamankazemi/2019/01/29/ai-big-data-advanced-analytics-in-the-supply-chain/#73294afd244f

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