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Tag: data analytics courses

How Big Data Is Changing The Way Marketing Teams Strategies?

Posted on by Imarticus Learning
Reading Time: 3 minutes

Big data in today’s world
Big data is transforming the way how the world thinks. Corporations have an appetite for data and they churn out almost everything from it be it vital or useless information, segregate the analysis on different parameters and draw out multiple conclusions. Today, we live in a data-driven world where everything from schools to offices, amusement parks to movie theatres runs, etc. runs on data.  Big data has become a very prominent turning point in the history of the world economy, therefore, knitting the world together faster and better.
Importance of marketing
Any company can produce a product or plan out to provide a specific service. The challenge is to take that product or service to millions of people who will then buy those products or avail those services, thus helping the companies to fulfill their ultimate objectives. In such a situation, Marketing comes into play. Marketing is a set of activities which are brought together to increase the mass reach of any company and its offerings. With everything shifting to an electronically operated platform, there is a strong gap that is constantly being filled with online marketing. Businesses are promoted online using multiple online channels such as search, videos, emails, ad campaigns, etc.
Big data and marketing
With the movement of the marketing function to a digital platform, its dependency on big data has become inevitable. Marketing teams of various companies analyze the trends prevalent in marketing using consumer data and come out with various new marketing campaigns to fill these gaps thus helping the businesses to meet and beat their targets. Companies are increasingly spending on mobile advertisements thus catering to a huge audience in a short period. These ads are individual-specific as Big Data Analytics Courses use the residing cookies in your system and display only those products and services which garner the attention of that particular individual.
Marketing and big data: a perfect blend
The advent of big data capturing the market, it has affected the marketing function drastically. It has made Marketing an interactive as well as a very insightful process. Marketers use tools like Google Analytics to know how their websites are performing and how many eyeballs their particular products are turning. Then accordingly they work on the marketing strategies of those range of products and services which are not performing well and also on those avenues which are outperforming to further increase revenues from them.
People spend long hours online thus making online marketing the only resort to reach the audience of this era. People are increasingly responding to online marketing campaigns thus bringing in more and more personal information into the picture. Big data helps in transforming these inputs into final sales and thus converting the desires of people into the business. The data collected in the online platforms will be the deciding factor for your marketing campaign’s success. Businesses will have no clue what’s going wrong in the absence of data.
Digital marketing and big data together have helped in improving the users’ product viewing experience. Marketing teams are constantly looking for new opportunities. Big data provides to be an effective tool in doing so. Also, it gives insights on when a company should pull the plug if something is working against its success. Using big data, every action can be tracked.
By reviewing data analytics, companies can find out how users perceive their business and its products. Using tracking codes, a lot of data can be collected and then segmented into various sections. Data can give minute details such as which ads are making the most revenues, which ads need improvements and which ads are working negatively. Also, companies need a record of conversions i.e. how many ad views are resulting in final purchases.
Conclusion
Big data is playing a major role in formulating marketing strategies. Data provides valuable insights that are further analyzed and developed into a strategy map on how the marketing function has to be taken up. Establishing concrete goals and measuring the fulfilment of such goals has become much easier with the use of big data.
For more details, you can also search for – Imarticus Learning and can drop your query by contacting through the Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Bangalore, Hyderabad, Delhi and Gurgaon.

How Big Data Fits In With The E-Commerce Customer Engagement?

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Reading Time: 3 minutes

Briefing the Big Data

If you are reading this wearing the glasses you ordered online, chances are that big data has some role to play in your purchase. If you are unfamiliar with the concept of big data reading the following piece of content here is going to add a whole lot to your knowledge base.

Big data can be understood as a big pile of the database that is amassed over time from various sources called data points, the big data helps in the identification of patterns, trends, and aid in providing useful insights for businesses and other parties in possession of the data. It is generally valued by big corporations to target their customers with ease.

The Virtual Customer

Big data is the norm today no matter what industry are you in, Big Data Training is the ultimate solution in the age of digital data and global consumers. Sales is a smooth sail in the digital ocean, courtesy of the big data!

The digital world has a new way of marketing things, different from traditional means of marketing the online and digital marketing expenditure has different components to it in terms of cost for content and creatives to lure in the targeted customer.

So how do you quantify and asses the performance of your marketing expenditure in the digital world? Well to address this query we have to dive deep in the concept of customer engagement in the dot com world. So customer engagement here unlike the traditional methods of marketing is counted through likes and comments and online traffics on the website.

Among the countless boons of technology, the one counted among the giants is enhanced globalization and making the concept of the world as a global village come to life. This has helped a lot of organizations to increase its customer base globally.

Talking about the businesses whose sole existence is credited to the merits of technology, e-commerce has a lot to be thankful for. Anyone who can connect to the World Wide Web could be a prospective customer.

To determine if you can target the one visiting the world wide web to come to visit your store needs a lot of insight about the visitor’s taste and preference his past track record of purchasing a product and the general trend of things, this is where the big data fits into the picture.

Big data boosting Ecommerce

What has been observed today is that customers are missing the human touch which can be understood in a sense as a personal attention deficit that the traditional brick and motor stores provide to a great extent. In the cutthroat landscape of eCommerce, you can’t just go with one size fits all approach, you have to style your market in a customized fashion making it more personalized for people visiting your E-stores.

Today the customer’s willingness to pay is not just limited to providing quality products, in the contemporary the game has changed altogether, people see everything as an experience, the better you polish that aspect of the business the more probability there is to gain a fair share in the market and retrain the customers.

Big data has amassed the data about all the variables that could possibly affect a buying decision. From personalized gifts to customized loyalty programs it delivers upon all the aspects of personalization that will generate new customers and will help retain the existing ones into the customer list.

Research has also shown that those who are using big data tools for their e-commerce business are likely to be more productive and efficient in their functioning. Big data not only delivers for the sellers on e-commerce but it’s also a magnificent time-saving tool for the customers as it helps them in a lot of aspects, from finding the right product to choosing the best fit.

Selling online is a different story, the big data pumps your marketing by only targeting those who matter based on the past records of purchase and preferences, and this naturally increases the conversion rates and the return on the marketing expenditure.

Conclusion

Big data is a game-changer for the e-commerce business segment given the presence and deep penetration of the digital world. Personalization of products and other customized services is enhanced to a huge extent with the application of big data.

How To Improve Your Supply Chain With Data Visualization Techniques?

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Reading Time: 3 minutes

Simplifying Supply Chain Management

If you have ever ordered a tangible good and got it within the stipulated time it’s because of a good supply chain management process in place by the company you ordered from. Supply chain management entails how a product is transferred from point A to point B, where point A is the place of storage and point B is the customer’s delivery address.

Supply chain management starts from the grassroots level, from sourcing raw materials needed for production to delivering it to the end consumer it covers every aspect of the product movement. The people working to manage the supply chain process have to carefully monitor the entire flow of goods and have to devise a strategy to help propel efficiency and productivity in the process.

The process has in its purview various sub-segments like sourcing, demand planning, inventory management, and logistics, the aim is to make the process smoother by individually focusing and renovating outdated methods of sourcing and distributing products to the end consumer.

The benefits of supply chain management range from increasing efficiency, cost minimization, and profit maximization to better demand planning.

All your e-commerce shopping expeditions are made possible because there is a supply chain process working 24 * 7 to facilitate your shopping spree.

What are data Visualization techniques?

With the advent of big data and the demand to present it to probable beneficiaries, the importance of presentation and formatting of data is utmost. It helps to weed out the unrequired information and highlight the ones that help the end-user to gain better insights.

The end goal of providing any data to the user is to allow them to gain valuable insights and take action using the same. Data visualization training deals with how to present the data in an attractive format to grab the user’s attention in a jiffy and help them to implement changes through the knowledge obtained.

Data digestion is important for the end-user to act upon the information, with so much information available on the World Wide Web, obtaining useful data can be tiresome and lethargic. The challenge for the data developers is to make it catchy for the eyeballs.

According to psychologist data visualization techniques help the user to learn better, photographic memories tend to last longer than plain texts.

Externalities like bad weather or accidents have a major impact on the timings of delivery and transportation of goods. To take into account such external factors the data visualization techniques help in mapping the geography and its indigenous externalities based on past records that might influence the transportation and shipment process.

Data visualization techniques for SCM improvement

Data visualization techniques help to improve and renovate the supply chain dynamics on a macro scale of things. Supply chain management has various components, from demand planning to doorstep delivery, everything can be perfected with data insights.

Let’s understand how data visualization improves supply chain management. So if we trace back to the core of the supply chain it all breaks down to identifying the perfect routes. Data visualization techniques can help to identify and demonstrate the details of the route and the alternatives present transport a product from point A to point B.

Plotting the complex relationship between various data points related to supply chain management through network charts and flow charts the pictorial representations enriches the content of the data.

Now the data regarding the routes might include the distance covered, time taken, traffic congestions, road construct, etc. So for identifying the perfect route, you have to factor in for all these elements and then reach a conclusion. How tiresome will be to dive deep into the subject matter? There come to visualization techniques that will help to put out the information in a precise manner catering to the needs of the user.

According to various research related to data visualization, it was found that companies are spending more on the use of immersive visual ecosystems to better their data visualization for the supply chain management. The benefits of the same have been reaped in the form of better inventory management and improved performance.

Conclusion

The implications of data visualization techniques in the field of supply chain management are enormous. From reducing time to analyze complex data to making more informative changes in a complex variable scenario the data visualization technique has changed the supply chain management landscape drastically. Improving the duration of transportation and delivery of products based on data insights factoring in various elements that might affect the situation.

What Are The Analytics Apps To Reduce Operational Costs At Production Facilities?

Posted on by Imarticus Learning
Reading Time: 3 minutes

What Are The Analytics Apps To Reduce Operational Costs At Production Facilities?

Introduction

Digitization has taken over the world with a storm. With numerous benefits, it has proved to be a boon for all sectors in which data is involved. Data analytics is shaping the world in which businesses are evolving. It makes data much more than stored figures. It brings out various trends and patterns of different segments of society. Data analytics courses can help businesses increase their revenues in multiples, optimize costs, Improve efficiencies, make cumbersome business processes much more simple and also using data in ways one could have never imagined.

Applications serving the purpose

Mobile applications have increased the use of data analytics. People use their mobile phones all the time thus making it easy for businesses to acquire a lot of individual-specific data daily. The app-space is huge and is coming up with innovations every second. Not a single area has remained untouched with this huge growth. From Real Estate to food, everything has analytics involved. This innovation has not left production facilities untouched. Analytics is making work at production facilities a cakewalk. Some of the major applications which have their hand in making work easy at production facilities are listed below.

  1. Dozuki

Dozuki is a standard work software that has changed the way the production space operates. Dozuki is dominating the visual learning platform by analyzing various trends and making videos on work instructions like repairing a car, opening a refrigerator, operating a piece of particular equipment, etc. This app makes use of images and video clips that are interactive and translates them into work steps and procedures. It is a very convenient application with a simple user interface. It is packed with everything you are looking for in a production-based application. It removes the complexities of a classroom training program where one can easily forget the basics of a particular procedure. The feedback option in the application is quite effective and the users can give their inputs on how they want their procedure videos.

  • Limble CMMS

The machine count in a production facility is huge. To manage all of the machines together is quite a difficult task. It is a maintenance software that a production facility needs. It monitors machines, equipment, spares and every other aspect which comes under such facilities. It keeps the machines running smoothly. Also, it optimizes the manpower cost which is involved in operating such giant facilities. This application is also rich in video content giving relevant information on manufacturing processes such as extraction, polishing, etc. It also has a simple and easy to use interface. It keeps a constant tap on the performance and productivity of machines. Such kind of applications also helps people to keep a tap on the physical maintenance of machines thus saving a huge cost which production facilities would have incurred on a sudden breakdown of any equipment.

  • Microsoft Power BI

This is a powerful analytics tool that can give insights on every aspect of a production facility. It can compile a huge amount of data on different processes and bring out relevant conclusions and process rectifications. The visuals are easy to understand and provides an in-depth understanding of various processes. It can automate the whole process by running various reports and publishing them in pre-decided time frames.

It removes the complexities of manual processes and makes production an error-free and smooth experience. This application has multi-fold benefits. It saves time and generates reports which can be easily deciphered by the people working in production facilities. Various metrics can be formed and tasks can be monitored with the help of automatic alerts. This helps people on maximizing the returns from the production function. In the end, everything is about optimizing costs and increasing revenues.

Conclusion

With every passing day, data is becoming a part of our lives. Analytics is shaping the whole world into a data-driven economy. With its increasing benefits, it is elbowing its way into all sectors and businesses. The production business is squeezing out everything it can and making the best use of data analytics in its day to day functioning and will eventually make itself a data-driven function that works on digitization and analytics.

What Are The Ways Big Data Is Changing The Healthcare Industry?

Posted on by Imarticus Learning
Reading Time: 3 minutes

Introduction

Big data is the new elephant in the room. One can do nothing but notice how fast its applications are increasing and talk about it. Big data has made use of such information which was collected through various systems but was never used. It is evolving with every passing day thus making itself a lucrative investment for companies who want to survive and flourish in this era of globalization and innovation. Big data analyses huge chunks of data a matter of seconds, thus drawing useful insights and also saving time, money and human effort.

The Healthcare industry

The health care industry includes everything from drugs to hospitals, diets to well being and a lot more.  The commercialization of the healthcare industry is growing at an alarming rate. It is one of the fastest-growing sectors involving almost the whole population of the world and loads of money thus forming almost 12% of the economy of any developed or developing nations. This segment has huge potential which was untapped until now.

With big data and analytics taking over the world, the healthcare industry has evolved tremendously. From medical insurance companies to drug manufacturing giants, all of them are minting money by using their data to the fullest, extracting out details one could have ever imagined.

The Healthcare industry and Big Data

The application of big data in the health care world has proved to be again for both – the parties providing services and the parties receiving the services. The big data uses the health data of millions of people to create a digitally empowered market. The big data has served its purposes by controlling harmful epidemic diseases and also curing millions of people. The major application of big data is in optimizing cost structures.

Various hospitals analyze the patients’ data available with them, finding out the intersecting points, working on them and saving millions. Various drug giants analyze their data with the help of big data thus improving their supply chain operations efficiently and increasing the reach of the medicines produced by them.

The health insurance market is a crowded space. The doctors make use of data to understand a particular patient, his medical condition and possible disease thus helping in curating the best insurance plan for that particular individual. This data also helps doctors in new findings and figuring out new innovative ways to cure diseases. Also, big data has not only made the analysis of data easy but also the collection of data a pretty convenient.

Data analytics also provide individuals like us to keep a tap on our general well-being and health. Various applications like Google fit keep calorie counts and heart rate information in data bits helping an individual to monitor his activities and also helping these big companies keep track of the lifestyle of their consumers.

Big data analytics training is helping hospitals to make staffing decisions so that they have an adequate number of people available when the hospital is oozing with patients. Also, this helps in tracking the hospital supplies and inventories like local painkillers, surgical equipment, surgery wearables, etc. It keeps the whole ‘Hospital-Ecosystem’ in check. It also helps in tracking real-time information and providing feedback on patients’ health regularly thus making the job of a doctor pretty convenient. Big data has brought the whole healthcare industry on a digital platform where details such as the medical history of a particular patient can be figured out in a fraction of seconds.

How this data is used by the Government

The government uses this data to chalk out the healthcare strategy for a particular country it belongs to.  This data helps the government in figuring out the number of hospitals, medical supplies, etc. needed by its people. This data can also be used in educating people about the benefits they can avail in terms of health care and well-being.

Conclusion

The healthcare is growing and this growth is not going to stop anytime soon. Like all other industries, big data is driving this growth and transforming the healthcare industry into a whole new world thus improving the decision making process and optimization of costs.

How ISPs Are Using Analytics To Help Customers?

Posted on by Imarticus Learning
Reading Time: 3 minutes

The world is driven by big data

Big data is everywhere. Businesses of all tastes and flavours are getting their hands on this mega resource to make their businesses competitive and also to gain useful insights that can shoot their operations to the zenith of success. Big data is loaded with multiple benefits. It churns up the data to bring out conclusions hence, giving a huge helping hand in making vital business decisions.

What are ISPs?

ISPs are nothing but people you need for the smooth functioning of your daily necessity: The Internet. Internet service providers are companies that provide internet services across various geographical locations so that people can access and use the web. This market is dominated by both large and small local players. The big players have the internet lines managed independently by them. The big players of this market are companies like AT&T, Netcom, MCI, etc.  These days a new group known as the online service providers has also come into the picture. They manage all of their operations through online mode.

ISPs and data analytics:

Internet service providers like any other sector are utilizing the applications of big data and making the most of it. Big data has become a profit-driving point for these companies. With the help of big data, the geographical boundaries are analyzed and then the reach of the internet and strength of signals and network concerns are also brought into the picture.

Analysis of data is done based on these parameters and then the expansion of business is carried on after several tests on feasibility, accessibility, etc. These providers use online advertisements to advertise their services, hence collect information based on clicks on the ads, their page staying time and their page abandonment time.

ISPs are using big data to have access to a gold mine full of data. Using analytics, possible customers are tracked down and then presented with an ad based on their individual preferences and search histories. These ads are curated automatically with the application of analytics. This data also helps in providing better customer experiences.

These service providers with the help of big data overcome the bottlenecks of Internet services such as network speeds, connectivity concerns, etc. Also, big data helps inefficient capacity planning and brings out operational excellence. Such mechanisms help these providers to foresee any upcoming issues and glitches which can make the users compromise on their user experience hence, solving it beforehand and providing a buttery smooth surfing experience.

ISPs are providing a next-level user experience with the application of big data and analytics. ISPs are using big data to mitigate a lot of problems and extracting the best out of what is available. The area which is compromised on a little is data security. Though the services providers are extracting out all the goodness of big data and giving an upgraded the internet experience to its users the data entered by its users are on huge servers floating, ready to be pounded on.

Data security is one of the biggest concerns which is bothering individual users. Users regularly feed information of personal importance and relevance to their smartphones and laptops. The data thus entered has no specific, safe place to go. It wanders in an unrestricted environment which can be extracted by anyone.

This problem is being tackled by big data to a certain extent but is being worked on so that the improvements can be made at a really quick pace in the area of data security and privacy of the users. Only data can protect data. Thus, these gaps are being filled up gradually by exploring more and more avenues of big data in this dynamic sector.

Conclusion

Internet service providers and big data are moving hand in hand. Both of them together are capturing consumer behaviour and extracting information out of it at an all-new level. Though there are certain limitations the ISPs and data analytics courses are jointly brought into force to eliminate such hindrances and emerge out with more upgrades. ISPs are sailing quickly and analytics is the captain of the boat driving it towards the island of growth dancing along the waves.

How Big Data Can Help Boost Sales?

Posted on by Imarticus Learning
Reading Time: 3 minutes

How Big Data Can Help Boost Sales?

Selling in general

Sales form the backbone of any organization. You need the revenue to soar up in order to quench up your profit maximization quest, that is what every capitalist aspires to do. No matter how good is the product or the services of a company, it will only grow the bottom line if it gets a good top line, i.e. sales.

Ever wondered how do salespeople close the deal and how do they manage to convert clients on the basis of leads? Well, the process is long and complex, it needs a lot of dedication and commitment to stay at the top of the game. If you ask a salesperson how did they manage to work wonders with a mere lead, the general response will be that they identified the needs of the customer and aligned it with the benefits provides by the products/ services they were selling.

A good salesperson knows the customer inside out and for that, you need to spend a considerable amount of time and money tracking the whereabouts of your customers and maintaining a personal relationship to some extent. You have to be a detail-oriented person who knows the nitty-gritty of things and is able to use the information to your benefit.

Sales in times of the big data

Sales in the times of the data revolution have changed drastically and more in favour of the salespeople easing their work with technology and insights. The above-mentioned approach to sales was commonplace until big data became the next big thing and technology evolved to complement this transition.

In the present scenario, whatever you need to know about your customer is available at your fingertips, thanks to big data. Name, number, email, address, etc. have become very generic and no efforts are required to gather the same. More advanced data about particular preferences, be it food habits or their personal hobbies everything and anything is available for those who use the World Wide Web and smartphones.

It doesn’t matter how insignificant a piece of information is, big data stores everything it can. Mostly the insignificant information about individuals combines to form a meaningful database that helps to obtain statistical inferences about a hypothesis.

For salespeople the big data is like a personal genie, they don’t need to wait long hours for meetings that might not even be relevant at the slightest in hope of conversion. Big data helps to boost sales by allowing salespeople to act upon the customer data available.

Big data Analytics Courses help salespeople by providing the required database to analyze past data and optimize their pricing given the demand and supply of the product or the services. It also aids in providing better visualization of the data to put in the right context. Other uses of big data in sales can be understood by the compelling case studies of the consumer.

What’s necessary for better conversion? Well, a good marketing stint of course. Marketing has evolved drastically over the past decade, with big data marketing that has eased the pain for salespeople through better targeting and advertising of the product and services offered.

From making predictions about what can sell well to designing the products that the existing customers need, big data helps a whole lot to make sales easier and more predictable than ever. Big data is also used to shape customer preferences.

The big data serves a special purpose for companies that are starting up and early in the process, it helps the companies to analyze data generated by the peers in the industry who already have been there for a significant amount of time and then helps to identify the loopholes and design their products and services better.

Conclusion

Sales are the backbone of every organization. You need revenue and profits to continue and grow your business empire, most of the expenditure related to operations is financed by the revenue generated through sales. In today’s scenario, big data plays a crucial role in increasing sales and in turn profitability of an organization. It helps the salespeople to target the right customer and design products more aligned with the needs of regular customers through its data insights.

How Predictive Analytics Help Troubleshoot Network Issues?

Posted on by Imarticus Learning
Reading Time: 4 minutes

 

Ten years ago, if a person had suggested a predictive model to prevent a network failure occurring due to a planned breach, people would have not believed him. Today, that has become a reality thanks to predictive analytic tools and different technologies including big data and statistical modeling.

In simple words, a predictive system looks for irregularities or patterns in data and identifies issues in a network or a server before they transform into bigger problems. This piece of information can then be used to troubleshoot it. An example would be a network outage due to failure in the power supply that can be predicted by looking at the irregularities in the flow of power supply in the days before the outage occurred. The possibilities are immense and that is why it looks so promising.

To make this clearer, let’s understand the basics first.

Analysis of Network Behavior

The basic premise of using predictive analytics to troubleshoot network issues is to let it analyze the behavior of the network. For example, analyzing the flow of data in a communications line can help it understand if any loopholes in it could create a possible entrance for a data breach.

This information can then be used as a preventive measure; a defensive mechanism can be laid out even before the breach is attempted, thereby safeguarding the data available in the line. This not only helps in the security but also in network management and policy setting. To know what is happening inside a server network and monitoring it is real convenience for network managers. It halves their daily maintenance work.

Additionally, analytics can also give out trends and insights to organizations. If a certain type of communication mechanism is known for overloading, companies can avoid creating similar structures and instead opt for better versions or entirely different infrastructures. This information can then be utilized during infrastructure development, especially when it comes to the development of server rooms for IT organizations where data breach and upper thresholds need to be monitored by the second.

Predictive Analytics in Action

Experts suggest that such technologies should be put to use in those sectors where issues can cause discomfort to a whole crowd of people. They are referring to healthcare and other emerging sectors like power distribution and aviation traffic management. Network management in these sectors will help increase safety and security and minimize issues/accidents.

Healthcare systems actually need this technology because it can help hospitals better care for their patients who require 24×7 technical support and are continuously connected to the hospital’s server.

Other than looking at the historical data provided by the network, other parameters like weather conditions are also taken into account. There can be a possibility that a thunderstorm could switch off a hospital’s network because of a power supply failure. If the effect of weather on the network can be predicted, then alternatives can be put in place just in time. Although such alternatives are already in place for emergencies, what such models will help in is better implementation and preparation.

A popular example is the use of predictive analytics in emergency services is how General Electric Power uses AI to manage its power grids in the US. According to this example, the predictive model helps the company get rid of the scope of manual errors in its system. It says that simple errors made at the service provider level can sometimes cause outages in the whole sector. This can be avoided if the data entry is taken online and passes through a filter that is connected to such a model.

Any mismatch in the data as compared to what is expected of it will trigger an alert and the response teams can quickly get in action. This is already being executed by GE Power even as it finds ways to make the entire grid system automated. This does not necessarily mean the absence of service engineers, but just the absence of potential errors that they are sometimes bound to make.

All of this is possible only because of the presence and availability of historical data. Without it, the predictive analytics models cannot compare the new tasks. This is one of the challenges that new sectors face as they do not have sufficient data to work on.

Some Challenges in this Field

Predictive analytics don’t fare well for environments that are rapidly changing. This means that environments where the relationship between two actions is quick, the model finds it difficult to grasp it and thereby ignores it and moves to the next action. This can pose a problem because it can lead to incorrect prediction, or worse, even dangerous predictions.

Availability of data, as noted above, is another hurdle but not something to be worried about. For sectors like healthcare, power, and retail manufacturing, there is abundant data. The challenge then is to source and save it properly which can be used to create the models.

Experts also point to the lack of implementation on the part of engineers. Scientists are continuously toiling to create predictive models that help in error detection but on-field engineers and workers are not supporting the system by providing or utilizing data. This can be a field engineer working on a local transformer for GE Power or a systems engineer at the grids network office not willing to listen to the model’s alerts. This shows that there is also a need for awareness among workers and engineers. This is definitely a radical change in how things work but embracing them is the only way to make it serve us better.

Predictive analytics, despite its active use in detecting and troubleshooting network issues, is still at a nascent stage in the global scale. While some countries and corporations are innovating in the field with ample help from scientific organizations, the practice will only strengthen when it comes to the mainstream. And that might take some more time.

How Can Data Analytics Help Insurance Companies Perform Better?

Posted on by Imarticus Learning
Reading Time: 4 minutes

It is the question that has already been asked after it was on everybody’s mind for a long time. How can big data help insurance companies – a heavily regulated sector in India and everywhere else in the world – and make them perform better? Especially when it comes to preventing frauds, system gaming, and other illegal activities that are prevalent.
With the competition only rising in the insurance sector, what company makes headway in properly using data analytics and acts a role model remains to be seen. So, in order for us spectators to do that, we will need more information.
How exactly can analytics help insurance companies serve their customers better? There are four major ways.

Use of Data Analytics in the Insurance Sector

Apart from gaining customer insights and helping in risk management, data analytics training can also help understand if it’s worth handing out an insurance policy to a person based on his social stature. How does his social media presence look like? What are his hobbies and adventurous choices? Has he lied in his application? All of this can also be extracted through the proper use of data capturing and analytics tools.
It seems extremely lucrative for the companies but it also poses a risk for us customers who stare at a possible invasion of our personal space and privacy. Having our social media accounts stalked by HR professionals for the purpose of employment is one thing (not a decent task, nonetheless). Having strangers do the same so that they can deny you insurance – which let us remind you is a basic necessity in today’s times – is a big event. It is not to say that this will be the majority outcome but it is what is on the mind of insurers when they consider big data.
Let us look at those four different ways in which analytics can help insurers:

Managing Claims

This is by far the biggest reason why insurers are pushing for use of predictive analytics in the sector. As you can imagine, it can help companies create a database of customer information that can then be used to compare new policy buyers and see if they fall in a bracket of people who might commit fraud such as wrongly filing for a claim.
The insurer can feed the model with past data and then use it to classify its new customers. Since the approval or rejection of a file is more or less under the authority of the insurer, this can help them denying insurance to a possible fraudulent applicant.

Generating Claims Based on Data

This involves checking the profile of a person while she applies for insurance. For example, in the case of house insurance, data can help insurers understand if this specific house is vulnerable to natural incidents; is it closer to the fire station; what is the history of the locality for the past twenty years as far as mishaps are concerned. When we talk about data, there is a lot of scopes.
And when it’s time to act, this collection of data can be extremely helpful to weed out fraudulent applications and other types of scams. It can also help them set better premiums if denying insurance is not an option.

Better Customer Support

Have you ever been in a situation where you have had to get your call to the customer care rerouted a couple of times before you finally got your problem heard? The call first moves to the respective section of the insurance (example: car insurance versus medical insurance), then it goes to the redressal section, and then finally you get someone on the other line to speak. It is extremely annoying for a customer. Even more so when she is in a situation where she needs urgent medical insurance support.
Big data can assist in this process by automatically understanding the issue of a caller and routing it to the respective section. This is possible based on the preliminary details that the customer has to fill in. The analytical model which is attached to the database of policies can better bridge the gap so that the customer gets her information quickly.
On the other hand, this can also help insurers keep a track on a particular customer. How many times in the past five years has she filed for insurance? What does her lifestyle look like now compared to when she bought it? This last piece of information can aid in guiding her should she decide to buy another policy with the same company.

Offering New Services

According to IBM, data analytics can also provide insurers with tools to market new products based on their requirements. Today, retargeting techniques and cold calling are used to push products to customers, but when companies have valuable data in their hand, they can easily club it with their marketing and advertising and even sales departments to better retain customers and make them buy more products.
This will require a lot of integration on the part of insurers, but the current market and the high competition say that companies will be willing to take the jump if they see there’s any scope to grow their customer base and tackle the menace of continued competition.
According to us, newer companies will be more desperate to try these systems out than incumbent ones that have functioned in the same way for years and even decades.
While we have talked about the scope in general tone, it makes sense to understand what specific tools will be of most use. Out of this, content analytics, discovery and exploration capabilities, predictive analytics, Hadoop, and Stream computing are some essential models that will pave the way forward for insurance companies.
Of course, all of this cannot be switched on one fine morning without the approval of IRDAI. The regulatory body is yet to come up with proper guidelines, and insurers will need to abide by those rules before they can start executing them.

How Is Data Analysis Used In Supply Chain Management?

Posted on by Imarticus Learning
Reading Time: 3 minutes

Supply chains today have gone global and spurred the growth of challenges and opportunities for suppliers, manufacturers, and others in the engineering industry (fondly called OEMs).To stay competitive lean and mean appears to be the name of the game. The rapidly growing automotive industry’s supply chain can be taken as an example of a supply chain discussed for the simple reason that its rapid growth makes it an excellent test case to study the impact of big data analytics courses.
The trend today is to perceive globalization, both as a challenge and opportunity and tweak its supply chain to create more agility, transparency, and visibility. Data analytics and that implies very big volumes of data and its analytics on a global scale, has been successful in managing and meeting deadlines of deliveries and production.
The supply lines stand improved, more efficient and productive through the use of Big Data Analytics Courses and invaluable insights garnered from data in assessing and decision-making, by efficiently gathering data, cleaning the huge volumes of databases, analyzing the required data sets and deploying the predictions and foresight offered by data.
To stay competitive in a variant-rich data-driven supply chain it is imperative that the supply-chains remain competitive while being productive and efficient on a global scale. However, even in 2017, the main issues with doing so was that the managers and planners were still unable to analyze, evaluate, and act on the data which was being generated and readily available to them. To leverage the benefits of a lean-and-mean supply chain is to effectively use and analyze data!
How does data impact the way a manufacturer, an OEM, or supplier works in the global supply-chain grids? What happens when data-driven supply streams are created and used well? How does strategy, based on data impact the operations of the company? How do big data analytics courses contribute? Let us briefly explore.

Greater organizational-wide insight

Looking at the big-picture and macro levels help organizations in data-based coordination, sharing and gathering for a pan-organization insight and context in decisions. Effective increase of touch-points, better contextual insights, and real-time monitoring has meant effective objectives, production benchmarks, outcomes, and goals. An increase in silo-making, collaboration, and communication in the supply chain adds value to the diversification and developmental expansion plans and ambitions of the automotive industry as a whole and occurs in real-time globally thanks to data analytics.

End-product quality maintenance:

Optimal production processes help data-driven supply-chains to produce better end-product efficacy and volumes. Data analytics has put the key to effective utilization in the hands of managers and planners to leverage resource allocation strategies, demand planning, scheduling, and inventory management. Developments like Industry V4.0 in Big data has also meant that OEMs can identify and monitor potential quality-control issues, access data-production and data details of processes, inspect in real-time the deliveries in-transit, and even check on scheduling and transit details of deliveries in progress. Thus risk-mitigation, improved efficiency, and greater productivity can be anticipated.

Surfing supplier networks:

The automotive supply-chain world over comprises of huge supplier networks that OEMs need to navigate, especially with the rapid proliferation of autonomous driver-less vehicles, smart-cars and electric vehicles gaining prominence and popularity in the rapidly fluctuating automotive manufacturing segment.
A data-driven supply chain allows for iterations in the complex OEM supplier networks while catering to its customers and evolves better products. Data analysis can also aid the S and OE level strategy making, allocate efficient production programs, link the facility capacity, and work around the production-floor restraints in dealing with ways and means of the inter-communicating process to ensure timely deliveries and smooth production.

Comprehensively treating supply-chain management:

Data analysis has the connective ability of disparate functions in supply-chain management which helps the planners and analyst to impact critical areas and cascade the effects up or down the supply lines. Thus data reporting can be effective in a ring-like interconnected structure where the impact and data analysis is successfully transmitted across the value chain. This also helps eliminate the barriers between disparate elements or functions and makes the supply chain more wholesome and vulnerable to change, holistic operations and data analysis.
For example, in the modern automotive supply-chain the various departments, services, and functions are effectively coordinated as a wholesome operation. Data analysis has helped in container management strategies, logistics, deployments, allocations, job-scheduling, routing platforms, inventories, and stock-management, etc and has successfully made the processes more efficient, productive and visible.
Conclusion:
Just as in the above example, you can also find your own value-adds to your specific supply chain by doing big data analytics courses at Imarticus Learning Academy. Grab the proposition to add value to your supply-chain and career. Hurry!
For more details in brief and for further career counseling, you can also search for – Imarticus Learning and can drop your query by filling up a simple form or can contact us through the Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Banglore, Hyderabad, Delhi, Gurgaon, and Ahmedabad.