Applications of Predictive Analytics in various industries

They say that those who do not study history are doomed to repeat it. In no form of big data analysis is this phrase more relevant than in ‘predictive analytics’. In simple terms, predictive analytics is the systematic use of data, machine learning techniques and a host of statistical algorithms to identify patterns that forecast the likelihood of future outcomes based on huge chunks of historical data. It is all about keeping a keen eye on what has and is happening to determine the best possible assessment of what might happen in the near future.

Predictive analytics slightly differs from other forms of big data analytics in that it is the only form that gives futuristic forecasts. Others such as prescriptive analytics gives directions on what actions should be taken to remedy various corporate issues; diagnostic analytics determines what happened and shows us why while descriptive analytics tells us what is currently happening.

Why Predictive Analytics is Crucial in the Business World Today?

Where big money is concerned, strategical mistakes can cost companies millions of dollars in revenue and operational costs. To avoid this sort of loss, businesses need to invest in forecasting.

In that entire chain of occurrences, you can already see just how inefficient the system can be. Solving these issues is critical and that’s where learning data science comes in handy. Especially, analytics that can forecast and help in strategic decision-making.Without predictive analytics, how can you tell whether or not the product you come up with will be useful to the masses? Without professional data scientists, how would you know who is most likely to buy your product? Which marketing strategies are most likely to garner you the most market share?

Minimizing inefficiencies through predictive analytics

The truth is, the world has been running on an extremely inefficient system. It only takes you looking at the statistics to see just how true this is to date. Up to 90% of all start-up companies fail: marketing tactics include casting a wide net that more often than not does not yield favorable results (out of 80 cold calls made, you would be lucky to get 3 sales), and the list goes on.

Over the last few years, most companies have taken a look at these numbers and realized that something must change. Companies are taking advantage of Big Data analytics, which is nothing but a culmination of Business Intelligence and Predictive Analytics, to attain an edge over their competition.

Here are a few applications of predictive analytics in industries:

Optimization of marketing campaigns

The Marketing campaigns have now become more optimized and efficient. Long gone are the days of ‘spraying and praying’ all the while wasting valuable resources trying to capture an unsuitable market niche based on a “hunch”. Today, through specialized predictive analytics, companies across the board can formulate effective strategies to identify, attract and capture markets for their products and services. The dependency on “gut feeling” has reduced.

E-commerce websites like Amazon have been making use of predictive analytics to capture usage patterns and past search data of website visitors to recommend products. A quick look around their website, or for that matter any other e-commerce player, will make you realize how predictive analytics is working so well. Amazon offers choices based on your likes and incites you to buy those products. From insurance companies to real estate, and almost every retail company, predictive analytics is now very much part of every operation.

Fraud detection

One of the main reason as to why predictive analytics has come to the forefront of the business world now is because the digital penetration has increased incredibly. Through big data analysis, there are systems in place that can combine multiple analytics methods to detect fraudulent patterns that indicate criminal behavior.

Today, one of the major concerns in the world is cyber security. With everything going virtual, to protect itself and its clients, major industry players such as banks, hospitals, social media companies and even police stations have resorted to using predictive analytics to minimize network breaches that could expose valuable information. Through the use of analytical methods, companies can detect vulnerabilities within their systems as well as abnormalities that indicate fraud.

Big online financial providers like PayPal have long used predictive analytics to determine what kind of precautions they have to take to protect their clients against fraudulent users.

PayPal uses data such as your historical payment data, to the kind of device often used as well as your PayPal user profile and country of origin, all these go into building machine learning algorithms that detect potential signs of fraud with every transaction.

Law enforcement agencies such as police departments on the other hand, feed off a large pool of data to police and protect the general public. From past criminal records/databases, to incident reports, crime tips as well as citizen feedback and CI information, the police can keep an eye on known criminals as well as potential acts of crime.

Reduction of risk

This is probably one of the very first examples of predictive analytics in action that most of us interact with on a regular basis. Every adult knows why credit score matters.

From banking to real estate, insurance, and even telecommunication, to get any form of credit or service nowadays, you need to have good credit. Credit risk analysis is all about big data.

Computer systems take into account all your past financial dealings and history and use that data to determine whether or not you present a high lending risk. It predicts how you will behave should you be lent any money. Some systems also show whether or not you do pay back your debts despite being labelled as a high risk. It is all about historical data and how you manage any financial mishaps.

Apart from money lending, predictive analytics is put to use by big insurance companies such as Liberty Mutual to determine the policy holder’s life expectancy and thus premium values This is all based on survival models created to predict just how long you will most likely live based on your lifestyle choices and pre-existing conditions. That is why they ask you those entire medical and lifestyle based questions.

It improves operations

Today, most companies use predictive analysis to manage resources and forecast inventory. For examples, airlines and big travel industry providers such as Virgin Atlantic and ‘Amadeus’ use predictive analytics to set ticket prices based on the predicted volume of traveling customers.

Hotels use such systems to determine future occupancy rates to adjust accommodation prices. Similarly, most retailers use similar systems to determine what discounts can be given, when should those promotions be conducted and to figure out the expected ROI of the promotions, etc.

Conclusion

From Oil, Gas and Utilities to Retail and the Banking sector as well as manufacturing and health insurance, everyone is relying on various predictive analytics methods to improve how they run their businesses.

The amalgamation of Data science and Analytics has transcended almost every sector.  applications of Predictive analytics are not only limited in innovatively supercharging business processes but also make the system more data-dependent than based on the gut feeling of the top management. Irrespective of whichever industry you belong to, if you look around the existing processes, you’ll find how predictive analytics helps in better decision making and if isn’t, then it’s time to make use of it.

The post Applications of Predictive Analytics in various industries appeared first on Big Data Made Simple – One source. Many perspectives..

As a globally renowned Business Analytics Consultant, we hold widespread knowledge in a comprehensive merge of the most contemporary technologies, frameworks and processes. Our skilled and experienced team of Tableau professionals have implemented a diversity of projects in Tableau BI. With enriched quality assurance to provide the best of services, we @ BizDataPro offer a range of Business Intelligence Services, Data warehousing, Big Data Consulting, BI Managed and Consulting services. Visit http://www.bizdatapro.com/ to get a feel of our enriched offerings, request for a free quote or arrange for a meeting with us. You can also read some of the case studies on Business intelligence solutions to have a feel of our expertise

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Discover how big data is implemented in business today!

Big data is a collection of very large sets of data that stream into a business every day. These sets can be structured or unstructured. Big data can be analyzed to reveal trends, relations or patterns in the behavior of a company’s customers. The analysis is conducted with the assistance of computer systems.

Big data has a number of characteristics. They include:

Large volumes: The amount of big data that arrives in a business is tremendous. This is because it comes from many sources all at the same time. Examples of these sources are transactions, social media sites, data from one machine to another and the information provided by sensors installed in the organization’s infrastructure. Due to the size of big data, special databases have been created to store it.

  • High velocity: Big data streams into a business at astonishing rates. Due to the high entry speed, special technology is needed to measure it in real-time. Examples of these are RFID tags, smart meters and high-response sensors.
  • Wide variety: This type of data arrives in a business in all types of formats. Some of it is structured while some is not. An example of structured data is numerical information while unstructured data is documented information. Other formats include video footage, audio files, email transcripts, stock data and financial information.
  • Variable nature: The flow of big data into a business normally changes according to conditions in the sources. Sometimes it can be low and at other times it can peak. Events such as viral content in social media can trigger massive peaks of big data. This can be hard to manage, especially when it is unstructured.
  • Highly complex: Thanks to its multiple sources, big data is highly complex. It is difficult to match, link and cleanse before being transformed for various systems. Substantial computing power is required to create relationships in big data, organize it into hierarchies and link data sets. Without the proper technologies in place, big data can become uncontrollable.
  • Databases are used to store big data. They are collections of data that is properly arranged such that it is easy to access, maintain and update. Special databases are required for big data.

Traditionally, we used relational database software to store data. They were built for Structured Query Language (SQL). Examples of these are Microsoft Access, Oracle RAC and MySQL database software. When big data entered the business scene, they were no longer powerful enough to handle the demands of this type of data. Therefore, computer scientists in conjunction with Remote DBA Experts created the NoSQL database software.

What is it?

NoSQL database software supports dynamic schemas. They are flexible, scalable and customizable too. They use four main methods to store big data. These include:

  1. Document storage
  2. Key-value storage
  3. Graph databases
  4. Column family storage

Examples of NoQSL database software include MongoDB, Couchbase Server, MarkLogic Server, RavenDB, Apache Jena and HadoopNoSQL database software.

It is important to note that you cannot simply install a NoSQL database to replace your relational one and store traditional data in it. NoSQL database software is made specifically for big data. This is because it does not have complete compliance with ACID (Atomicity, Consistency, Isolation and Durability). This compliance normally guarantees the integrity of transactions and consistency of data. Due to the nature of big data, ACID compliance was relaxed. This maximizes the ability of NoSQL database software to collect and manage big data.

Why is NoSQL database software used for big data?

This type of database software does not utilize the usual elements that we are used to seeing in relational databases. There are no tables, columns or rows. Moreover, you do not need a schema to design and create a NoSQL database. This type of database software is designed in this way so that it can provide you with rapid access to real-time data. This sort of access empowers you to run real-time programs for your business processes. An example of this is in the stock market. NoSQL database software organizes data using new formats that were not utilized traditionally. The lack of a schema allows you to interact directly with massive amounts of data, saving you time and money.

Impact of big data in business

It has rejuvenated traditional industries

This type of data has transformed various aspects of traditional businesses. By injecting the power of information, it has refreshed them. Big data affects various departments of a business. Examples are the customer service and supply chain departments.

Quite a number of traditional enterprises have gained substantial benefit from implementing big data. An example is the Rolls Royce Corporation.

Well known for their automobiles, Rolls Royce also manufactures aircraft engines. Traditionally, these engines needed to be inspected in hangars. Today, the engines have hundreds of sensors that monitor their performance in real time. The sensors send engine data to Rolls Royce through big data infrastructure. In this way, the company has leveraged big data in its operations and increased revenue by selling engines and engine-monitoring services in one package. These packages account for over 70% of the company’s annual revenues.

It has created a brand new industry

Traditionally, data was collected simply for reference. Managers and accountants referred to it for the purpose of justifying investment or knowing the progress of the company. Today, big data can be collected for the purpose of profit. Whoever is able to collect and cleanse as much big data as possible can sell it to other companies for a fortune. Stakeholders in the IT industry have discovered this and many are establishing startups whose primary objective is the collection and sale of big data.

Conclusion

Big data is here to stay. By investing in the database software indicated above, companies can reap the benefits of using big data in their business processes. It has even created an industry that is attractive and lucrative.

The post Discover how big data is implemented in business today! appeared first on Big Data Made Simple – One source. Many perspectives..

As a globally renowned BI & Big Data Analytics company, we hold extensive experience in a multifaceted blend of the most modern technologies, frameworks and processes. With enriched quality assurance to provide the best of services, we @ BIZDataPro offer a range of Data warehousing, Big Data Consulting, BI Managed and Consulting services.  You can also read some of the case studies on Business intelligence solutions to have a feel of our expertise.

Top 8 Revolutionary Trends in BI Analytics to Watch For

Business Intelligence has been an indispensible ingredient for most enterprises today, crossing the inhibitions of the size of the business or the industry domain to which it belongs to

Business Intelligence has become one of the most talked of technological concept today and is all ready to become the most innovative and indispensable technology too. Hardly would you find enterprises that are yet to implement BI in their businesses, the prime reason being the unstoppable data that is being gathered yesterday, today and tomorrow. Ever increasing in volume, this data needs to be treated and relevant information needs to be extracted from it – a need of all organizations barring the size and industry segment they belong to. Business Intelligence strives its best to understand all these varying pieces of information, attempts to put them together and give a meaningful and analytical piece of information, in the desired format, in the desired time at the desired location. The perfect blend of BI & Analytics, clubbed with Big Data ensures no data untouched, unprocessed and give you the ideal output. It focuses on an amalgamation of processes and technologies to extract, store, analyse and transform data into enriched information. Technology giants have invested their expertise and experience in BI – Microsoft BI, Tableau, Pentaho being the major ones.

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The recent year has seen a massive shift towards the latest trends in BI and Data Visualization, with organizations leveraging its potential to the fullest and thereby witnessing novel trends and technologies being a part and parcel of routine business processes, gaining deeper insights into their information arena and garnering the much required information quite easily. Enterprises are moving onto to fully fledged BI & Analytics platforms, creating enhanced business value, increased productivity and maximized ROI.

With BI marking its place with a trump, there are supporting elements like the social media, mobility, cloud services, Internet of Things, Internet of Everything and other data technologies that are supporting the growth of BI in the globe and are all set to plunge in their technology threads to weave theirs with this technology giant and bring about a fresh new technology that the globe goes gaga over. The current trends in BI and Big Data Analytics showcase innovative elements in BI clubbed with other technical components bringing about revolutionary concepts its way.

8 Most Innovatory Trends in BI and Data Visualization

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  • Data Mining and Integration Gets Moving Faster

Data Mining and Data Integration form the crux of any BI solution and with BI raising exponentially, both these techniques are bound to get a power boost. There has been an observable rise in sophisticated tools to support them gathering in every bit of information that comes on the way. It is now ensured no data goes waste. Each and every bit of data is analysed, visualized and analysed up to the core. Latest trends in BI and data mining reflect the growing importance of the data related techniques and its foreplay in implementing BI & Analytics, whatsoever may be the industry domain or the size of the business.

  • Self Service BI & Analytics

What is most important in any technology is not only the technical sturdiness and features, but how well does it gel with the end users, especially the non IT staff. It is very much required that the BI solution should be able to reach the most important set of end users and should be accessible to them in their own way, rather than depending upon solution providers. New trends in BI analytics focus on a section of users who, despite less know how of the BI tool, are able to operate the solution and extract the desired information themselves, without any external help. Self Service BI has been garnering a lot of attention and affection both, since it relates to the masses and hence is increasingly getting popular. Self Service BI is continuously evolving to attend to the requirements of the agile enterprises and is no longer bound with static reports as offered by IT. Now it calls for building your own reports, your own way, exploring within and then interacting with it, drilling down to the deepest level possible.

  • Internet of Things and Data Science

The Internet of Things (IoT) and Data Science are a bare reality today and we are very much engraved in it. The huge heaps of data that gets generated is getting larger day by and day and hence the powerful blend of the IoT data along with BI and Big Data analytics are a sure shot way to get the best information possible. The IoT is a world in itself and hence has the potential to create a lot many opportunities for data visualization and real time analytics. With Data Science becoming the latest talked about technology, it offers a large amount of predictive analytics to give a glimpse of what is in store for the future.

  • Cloud BI

Cloud BI is a foreseeable accomplishment roadmap for best business suppleness determined by two of the most popular technologies – the Cloud computing with Business Intelligence. This has gained momentum today and organizations have started adapting it. Cloud BI is turning favourable for smaller organizations that are able to adapt BI technologies with ease and cost effectiveness, since they no longer need to set up internal teams to maintain and monitor applications. The major advantages being noticed are ease of use, deployment speed, scalability, elasticity, and accessibility.

  • Enhanced and Flexible Data Visualization

Data visualization was always there, but now with the invent of BI and Data Visualization tools and techniques, there have been umpteen better methods and ways to extract various kinds of dashboards / analytical reports through innovative techniques. ‘What you see is what you perceive’- so rightly said. It becomes easier for enterprises to read and interpret information now. Eyes have now moved on from the typical rows and columns data to visually appealing, graphically enriched reports.

  • Internet of Everything

Now, the buzzword goes beyond Things to Everything. Not only IoT, the globe is trotting towards IoE. The current trends in BI are now pointing towards Internet of Everything, which focuses on availing information not only from devices, machines and sensors but also gets in information from logs, geo locations and data from the net. The flawless amalgamation of IoT, IoE, Big Data and BI Analytics form the crux of the success of any business.

  • Mobile BI

What is today’s world without Mobility? Just unimaginable. So extensive is the penetration of mobile devices into our lives that it is impossible to go on without them and no wonder, BI gets into mobiles too. Any device, any time and any platform integrated seamlessly with any information, any format and any time is what is termed as Mobile BI and that is creating waves today. A trend in itself, this novel methodology operates through a mobile browser directly accessing the application either on the web or through a native app.

  • Penetration of BI into major business domains

The latest trend being observed today is that BI & Analytics is penetrating seamlessly into all major industry segments now. There are hardly any domains who haven’t yet tasted the success of a Business Intelligence solution. BI trends in Healthcare are showcasing valued solutions in many peripheries like hospital data management, medical practices workflows, patient relationship management, clinical / financial analysis of data, research and others. BI trends in Retail Industry are focussing on penetrating novel sales channels, reaching consumer needs, management of ever changing data and taking enhanced business decisions. BI trends in eCommerce have also proven successful in availing desired information, cross selling and up selling through eCommerce websites, along with a variety of reports like sales trend analysis, customer buying track records, sales and revenue report management, sales evaluation, marketing campaign effectiveness and market demand prediction.

These are just few of the many highlighted trends being observed for BI and Analytics. There is lot more to come. Wait and watch till it penetrates deep into each and every business arena and makes itself an indispensable ingredient in the business success formula. And, something to really look out for is the unblemished integration of all these powerful giants – BI, Big Data, IoT and IoE. Soon, you will find all of them working together collaboratively and amicably.

 As a globally renowned Business Analytics Consultant, we hold widespread knowledge in a comprehensive merge of the most contemporary technologies, frameworks and processes. Our skilled and experienced team of Tableau professionals have implemented a diversity of projects in Tableau BI. With enriched quality assurance to provide the best of services, we @ BizDataPro offer a range of Business Intelligence Services, Data warehousing, Big Data Consulting, BI Managed and Consulting services. Visit http://www.bizdatapro.com/ to get a feel of our enriched offerings, request for a free quote or arrange for a meeting with us. You can also read some of the case studies on Business intelligence solutions to have a feel of our expertise.

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