The rapid growth of technology has led to many people opting for online services, and thus the collection and maintenance of data becomes a significant factor for any company. Big data analytics service providers can help the companies get a massive edge over their competitors as they would manage the data well and allow the businesses to make better business decisions. It will provide you with a combination of increased customer experience, revenue, and reduced cost and thus will create a win-win situation for your business. Big data technologies will be your perfect ally in excelling in the cut-throat business environment and come out with flying colors.
Big Data Analytics is a growing field, and many companies are interested in it. Businesses have understood that they are wasting a golden opportunity by not collecting and analyzing the data they receive from their customers and visitors using Big Data. It is not just that Big Data as a technology is trend, there are various trends in Big Data as well that are doing the rounds and catering the best piece of the cake to the businesses based on various industries.
The growth of big data market is expected to be phenomenal, and according to a report by Frost and Sullivan, the data analytics market is expected to grow at a CAGR of 29% to $40 billion by 2023.
This explosive growth has prompted many Big Data Analytics Firms to come up with great solutions. Having a leading company providing the best Big Data Services to solve your issues and to gain the immense benefits that big data analytics offers can help your business go a long way.
Before you dive into the exciting world of Big Data, it is essential to know some basics.
Types of Big Data Analytics
Descriptive analytics deals with summarizing raw data and converting it into a form that is easily digestible. Also, by using descriptive analytics, one can easily infer in detail about an event that has occurred in the past and derives a pattern out of this data.
One of the most crucial data analytics, descriptive data analytics helps in revealing critical information about a business. It is impossible to create ideal Business Intelligence tools and dashboards without conducting robust descriptive analytics.
Descriptive analytics helps in addressing some fundamental questions of data analytics (4Ws One H). Descriptive analytics contains two subsets, Canned Reports, and Ad-hoc reports. While a Canned story is a report which includes information on a particular subject but on previously designed parameters like monthly reports. While an Ad-hoc report is not pre-determined and is more of an ad-hoc thing.
In an ad-hoc report, you can attain in-depth information about a specific query. For example- an ad-hoc report can help you in identifying the types of people who have liked your page. The hyper-specific nature of an ad-hoc report will help you in gaining previously unseen insights into your business.
In diagnostic analytics, we explore a specific situation in-depth to identify the root cause of a problem or to explore an opportunity. In diagnostic data analytics, we examine a particular data set and try to ascertain a cause-effect relationship.In diagnostic data analytics techniques like data discovery, data mining, and drill-down are employed.
There are two main categories of diagnostic data analytics.
One is the discovery and alerts category in which the primary purpose of analytics is to notify the concerned people about a potential issue before it arises. For eg, it can alert a purchase manager about the low quantity of raw material beforehand. We can even use diagnostic analytics to discover something particular like who will be the best person for a specific job.
We use Query and drill-downs to know in detail about a particular event. For eg, if you notice that the productivity of a few employees has dipped, then on conducting a query and drill-down analysis, you will identify that they were on vacation.
Similarly, you can identify why sales have decreased or increased over a specific period. The ability of diagnostic analytics to give you insights is limited as it can just provide an understanding of a causal relationship.The primary purpose of diagnostic analytics is to determine the causes of a particular event by comparing it with past events. One can use diagnostic analytics to identify the outliers, to isolate the patterns, and to uncover the relationships between various activities.
Predictive analytics is the type of data analytics which tries to forecast the future trends based on what is happening in the present, instead of focusing on the past. Predictive analytics also helps in estimating when the event will occur in the future.
Predictive analytics is commonly used in the healthcare industry to assess the probability of a patient contracting a disease. For example- based on lifestyle choices, habits, environment, and genetics, a predictive algorithm can determine whether the patient has a risk of heart failure or not.
Predictive analytics is the outcome of your descriptive and diagnostic analytics, where you turn the insights gained from these two analytics into actionable steps. Predictive analytics helps in describing what will happen if certain conditions are met.
The predictive analytics tools help your business in taking a peep at the future. They help in predicting and planning for the future. You can also enable statistical modeling using predictive analytics, but bear in mind that to harness the full power of predictive analytics, you will require using Artificial Intelligence and Machine Learning.
While conducting predictive analytics, take enough care that the data that you input is accurate as even small inaccuracies can extrapolate and lead to significant mistakes in the output.
In prescriptive analytics, you will go to the next level of data analytics, as you will evaluate a large variety of options and see how you arrived at a particular outcome. A pretty standard example of prescriptive analytics is the GPS app, as it looks at various available route options before zeroing in on the best possible route towards your destination.
The prescriptive analytics helps you in moving up the data analytics maturity model by allowing you to make fast and effective decisions. Using new techniques like Machine Learning and AI prescriptive analytics can help you in trying the various possibilities without actually spending time experimenting with all the variables.
Prescriptive analytics helps you in identifying the right variables quickly, and it even suggests new variables. The primary purpose of prescriptive analytics is to advise you on the next action to take so that you can eliminate a future problem.
Many tools, like Machine learning and sophisticated algorithms, are required to implement prescriptive analytics properly. Hence it would help if a cost-benefit analysis is done before going ahead with the implementation of prescriptive analytics.
Prescriptive analytics can suggest outcomes based on a specific course of action and also suggest various tracks to get your desired outcome. Prescriptive analytics uses an active feedback loop to continually learn and update the relationship between a particular cause and action so that it can predict the future with sufficient accuracy.
Big Data Analytics is changing the way businesses work by using predictive analysis which helps to gather insights related to improving ROI and provide seamless solutions.According to research, it is found that about 1.7 megabytes of data will be generated every second, and there will be 3.5 billion search queries on Google every day by 2020. The humongous data is a clear indicator of the importance of better opportunities that businesses will get with Big Data. Also, companies are expected to spend over 57 billion dollars this year for Big Data to become more competent in their craft and stay ahead of the competition.
Modern-day businesses should understand the fact that if they use Big Data Analytics prediction to its optimal level, it can boost their brands and provide valuable insights related to consumer behavior. As the world continues to lean towards digital technology, data metrics are generated at an even faster rate. It means that you can enhance your business by using data analytics and find out the buying patterns and likes and dislikes of your customers on both individual and mass-scale basis.
Big Data analytics predictions will guide the business organizations to create opportunities so that they can grow dynamically with the help of astutely analyzed data. The companies would have better chances with Big Data, as there will be ample information about consumer preferences, buyers, and supplies that can be analyzed for future benefits.
A brief history of Big Data
While the term ‘Big Data’ seems to be relatively accurate in the business scenario, the concept of collecting data in large numbers started years ago. In the early 2000s, industry analyst Doug Laney coined Big Data as the collection of three different things.
Variety: For businesses working in different domains, data can come in various forms from various sources. The variety here concerns all the heterogeneous sources of data, both structured and unstructured. Previously there were only databases and spreadsheets that were considered as data sources, whereas emails, videos, and monitoring devices form the new age data sources.
Volume: As business organizations have data coming from a variety of sources, the storage of data in a synchronized manner can be a problem. The new-age data analytics in business uses technologies such as Hadoop so that data can be saved in proper order and can be used by the organization as and when required. Volume is a clear indicator if a particular data can be considered as Big Data or not, as all will depend on the size of the data.
Velocity: The velocity in Big Data depends on the speed at which the data is generated in Big Data. Velocity ensures that the flow of information is continuous and in a substantial amount.
How will Big Data prove to be a vital cog in any of the Modern-Day Business Organization?
Reducing the Cost
The predictive analysis tools in Big Data Analytics like Hadoop are very cost-effective and bring many advantages to the businesses when there is a large amount of data. The tools will identify effective manners in which the data can be stored, and businesses can have better opportunities. With Big Data Analytics, companies can take better business decisions to expand their base.
Marketing and Advertising
With better data analysis, the businesses would have a better understanding of the market and the likes and dislikes of their targeted audience. Using the power of Big Data Services, businesses can make more effective advertisements by analyzing the likes and dislikes. The data analytics in business will enable the companies to find the products that they have sold the most and thus produce more products accordingly. Better opportunities with Big Data will keep the businesses a step ahead of their competitors.
Online Reputation Management
In today’s connected world, your company’s reputation online has the power to make or break your company. The most significant advantage of conducting Big Data predictive analysis is that the tools can prove handy in performing sentiment analysis. You can get feedback about products and also know who is saying what about your organization and its work ethics. Big Data tools can also help in monitoring and improving the online presence of the business. By monitoring analyzing social media pulse, you can know in advance what your customers are thinking about your business. As your online presence will increase, it will improve your chances to be in the limelight and enhance your user base.
Reducing the Time
The high-speed tools will make the big data predictive analysis take the execution process to a whole new level and complete it in a brief period. Tools such as in-memory analytics can easily find new sources of data. It will help the business organization to complete the analysis process in less time and make quick, accurate decisions based on the learnings from the data.
Innovative Product Development
With correctly analyzed data at your side, the organizations can go full throttle in innovating things and products according to the likes and dislikes of the targeted audience. Big Data is transforming businesses as it is helping the firms to redevelop their products in a better manner based on the data of their past performance. It will provide a substantial upper hand to the companies using big data predictive analysis and expand their business by leaps and bounces.
Managing Business Risks
Data analytics in businesses promotes action plans that are driven by data and have very less element of risk. The data analysis will make targeting audiences easier for companies of all shapes and sizes by using Big Data. The actions taken based on data are more quantifiable, compact, and result-driven. This kind of strategy saves businesses from high-risk situations and refrains them from making unnecessary risky decisions.
You will find information from all possible sources in a synchronized manner, and thus it will help in getting to the core of the market and make your business plan accordingly. Data from social media platforms and other sources will help the organization to devise the best possible business strategy, which is foolproof and can be moulded according to the changing trends of Big Data.
The management and the usage of data have changed in the industry since the inception of Big Data Analytics. Out of all...
Historically, healthcare is one such industry where you require data analytics in a substantial quantity. You have data related to previous health records of patients, hospitals, doctors, etc. The inclusion of Big Data in healthcare analytics has reduced the cost of treatment drastically.
In addition to this, Big data companies will analyze the sizable data provided by the hospitals and authorities. They are thus making it easier to predict the outbreaks of epidemics and improve the quality of life.
The amount of data related to healthcare is continuously increasing. Therefore, for doctors and hospitals, it is becoming increasingly challenging to manage this data through traditional data management tools or methods. The data related to healthcare is diversified, and you can leverage the expertise of a Big Data analytics company to do this analysis with precision and speed.
The triggering question coming to your mind must be that what are the kind of obstacles that one will face in managing data in healthcare? We will find the answers and how big data analytic technology will help the healthcare sector to find these answers.
The need for Big Data Analytics
The cost of healthcare is constantly increasing in nations for the past few decades, and thus there is an acute need for a smart data-driven thinking process in this area. The data-driven process helps the hospitals and the doctors to keep track of the progress and diagnose the problem in a better manner. As there is a requirement of astute data, there is no room for guesswork or hit and trial process from the hospital or the doctor's end. The paradigm shift provided by the Big Data Analytics is bringing pharmaceutical companies and hospitals, etc. towards a pool of data that is effective in finding things in a precise manner and bring changes at an extraordinary rate.
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