How Top Companies Use Big Data Technology!
Networks and corporate connections are beneficial for any organization to do business but, the central pillar for developing & growing business is the organization’s internal know-how accumulated through understanding their business and the customers. This is true not just for online businesses but also for any business doing any activity online. That means, while making key business decisions, all organizations rely on the data that they can collect or generate.
Therefore, companies these days accumulate and analyse data with even more urgency to surge ahead of the competition. Market surveys are done by big consulting companies also point towards the trend of organisations placing increased emphasis on making data-backed decisions. The ultimate goal of the organization is profitability. Assuming the fact that every company acquires a different approach towards getting benefitted, dedicated research projects are carried out to find out the most proficient delivery methods. For instance, a leading bank utilizes big data to keep track of frauds and to keep the same in check.
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A renowned insurance firm has established a dedicated data science team to resolve anything pertinent to any kind of claims & customer loyalty. Furthermore, Top companies use Big Data technology to retain clients and make them keep coming back. The fact is, be it virtually any industry, data-driven decisions are helping firms to accomplish profitability.
Reasons Why Top companies Use Big Data technology:
Top companies use Big data technology for making better decisions. This data helps in enhancing efficiency and business operations.
- Organization’s aim to augment the overall productivity
- Enhancing client’s comprehension, their requirements & patterns of purchase
- Contribute towards profitability & revenue generation
Also Read>> Key Challenges Organizations Face When Implementing Big Data
Now let’s have a look at how all the top-notch organizations are utilizing Big Data:
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T-Mobile
Telecom giant T-Mobile accumulates huge data through smart devices & gadgets like phones, tablets, etc. and it utilizes the data to keep a check on client turnover. The company has successfully accomplished a 50% decrease in turmoil & chaos by implementing the analysis & keeping itself at the peak in the fields like geographical usage trends, client purchases based on location and client lifetime value. The distinct strategy that the company implements is Social Networks, as they can make an impact on various other telecom choices and in revert, these influential clients are provided with perks.
Starbucks
Coffee chain front-runner Starbucks possesses the capability to sustain an incredible number of locations within immediacy to others, which is a significant function of Big Data. To comprehend this more, we can take an example of two Starbucks coffee outlets in very near proximity to each other. This is not a coincidence; as they have been placed like this deliberately based on the big data, demographic information, traffic analysis and other pertinent details. The purpose behind opening many stores in close proximity to each other is that Starbucks works on “Squeeze it” principle. It creates an entry barrier for competitor brands in a specific area and based on the demographic analysis captures the footfall.
Capital One
The company called Capital One is implementing & analysing behavioural data to outline client offerings for ages. The optimization engine conducts an analysis of client demographics & purchase patterns of users so in order to evaluate where, when and how to introduce offers & schemes to customers resulting in enhanced revenue generation along with a satisfying experience for customers. The organization also takes initiatives like setting up labs, which is a technology-driven think tank with the help of which, professionals can utilize big data to sort through promising opportunities like various ways of mobile banking as huge data can be accumulated through specific mobile applications utilized by users and pertinent information provided on call of actions through these smart devices.
Free People
The apparel leader Free People utilizes infinite clients records, which are then processed by in-house analytics to comprehend the pattern of purchase and offerings for the next season. It read what was sold the most, what product didn’t sell at all, what was returned and what products actually enhanced the brand image of the organization.
Conclusion
What all of the above-mentioned organizations have done is that they have yielded maximum benefits out of big data which eventually results in accomplished goals. Centre point is organizations need to understand their key business objectives and realise the same with the massive potential of big data. Lacking a proper vision, organizations might invest money and resources in big data collection but in that case, the outcome will not be any more than numbers.
Giant & globally reputed organizations like Accenture, Oracle, PWC, SAP, DELL & HP and so on are also reaping the benefits of Big Data accumulation and analysis. Top companies that use Big Data technology is no longer a novelty, but not using Big Data can severely hurt the firm’s chances against its competitors.
Also Read>> 5 BIG DATA CONCEPTS!
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FAQs
Why do businesses use Big data?
Businesses are using big data to gain a competitive edge. With the help of big data, the decision-making process becomes faster due to the availability of a huge amount of data. Businesses are also able to analyse what their clients want by analyzing the collected data. Such data also helps in understanding consumer trends and take business decisions accordingly.
What are the different steps of deploying the Big data model?
There are three key steps involved in the deployment of the Big data model. These include: 1. Data ingestion: data collection from different platforms. 2. Data storage: storing a large amount of data post data extraction. 3. Data processing: Analysing and visualising the stored data through algorithms for data processing.
What are the different types of big data processing techniques?
There are four techniques of Big data processing: Batch processing of Big Data, Big Data Stream Processing, Real-time Big Data Processing and MapReduce.
When do we use MapReduce with Big Data?
MapReduce is used for selecting and querying data in HDFS. MapReduce is useful for iterative computation which involves a huge amount of data that requires parallel processing.
What is overfitting and how to avoid it in Big Data?
It is an error in modelling wherein a model function is tightly fitted to a limited data set due to which predictivity of the model is reduced. Due to overfitting, generalization ability is also reduced. To avoid overfitting, methods like cross-validation. early stopping and regularization are used.
What do you mean by Features Selection?
Feature selection is a process of extracting required features from the Big data. This process is used when we only need to work on a few features at a time.
Explain the different types of feature selection methods?
There are three main feature selection methods include: 1. Filter method: this is the variable ranking method in which only the importance and usefulness of a feature are considered 2. Wrappers method: This is a method for producing a classifier using an induction algorithm 3. Embedded method: This combines the efficiency of both the wrappers method and the filters method.
Explain missing values in Big Data?
These are the values that are not present in a column which leads to incorrect results due to the erroneous data. Mean imputation, Multivariate Imputation by Chained Equations and Random Forest are the techniques for dealing with such missing values.
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