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Big Data and Analytics: A Look at Industry Direction and Use Cases

Posted by Michael Roush on Jun 7, 2017 10:00:00 AM
Michael Roush

The era of big data is well underway in 2017. This presents a strong opportunity for you to capitalize on the growth in this sector of technology. Worldwide spending on big data is at an all-time, according to IDC, as multi-industry adoption of big data and business analytics continues to grow as a priority.

Big data represents an estimated $150.8 billion of the overall spend for Third Platform technology this year alone. This upward trend will continue over the coming years (to $203 billion in 2020), as more and more companies understand the short and long-term returns gained via business analytics.

Use Cases for Analytics

The key to gaining a foothold in this growing market is understanding use cases where business analytics are applied to big data in order to make strategic business decisions.

  • Telecommunications: Predicative analytics for network usage are the foundation for the telecommunications industry’s ability to optimally serve their customers. By aggregating the data on geolocation of network subscribers and peak usage dates and times, telecommunications companies can make informed decisions around the most cost-effective investments for their network infrastructure.

  • Security: Businesses, regardless of sector or industry have become securitized – meaning existential threat is posed to their financial and intellectual property from internal and external actors. Security-focused behavioral analytics arm business with a myriad of tools to preemptively reduce security risks. For instance, a business can use password usage analytics to monitor password sharing among employees, or other security policy violations, and correct the behavior prior to a major security lapse. Behavioral analytics can also be employed to detect compromised user accounts affected by phishing or malware by identifying small changes in behavior and enabling the security analyst to intervene before additional users or data are compromised.

  • Retail: The retail industry has numerous use cases in which they can improve the customer experience and optimize the buying process. By analyzing the massive amount of clickstream data on their websites, retailers can optimize the user experience and make buying easier. When it comes to in-store experience, the new Amazon Go model eliminates the need for customer checkout through an aggregation of data. This data is generated from in-store sensors, machine learning, and cloud computing, allowing customers to grab their items and go, and Amazon charges their accounts as they leave the store.

  • Financial Services: Banking, insurance, and securities and investment services are the biggest industries of opportunity for data analytics. Fraud protection is a key driver of big data adoption in the financial services sector as financial institutions are increasingly required to stay a step ahead of fraud activity. By analyzing transaction and geolocation data, financial institutions provide a stronger value-add to their customers by drastically limiting the size and volume of fraud.

Tech Data as a Facilitator of Change

According to McKinsey’s Jacques Bughin, there are five managerial and organizational best practices for maximizing the ROI from big data adoption within the telecommunications industry. However, these recommendations can be applied across numerous other end-user industries.

  1. Adopt Big Data best practices before you have to. Meaning, implement this technology proactively and reap the benefits once the amount of data a company has to handle grows exponentially.

  2. When spending money on big data use cases, money should first be spent on the right IT architecture to reap the complementary benefit of big data talents. This notion is not one of replacing data capabilities, but rather to make sure that data scientists have the right IT architecture, tools, and data to deliver their insights.

  3. Big data should be put high enough in organizations to allow traction and favor end-to-end synchronization between users and big data producers.

  4. Companies should invest in multiple use cases.

  5. Digitization helps adoption of big data, provided the big data projects are well managed.

Tech Data is poised to provide our reseller partners and MSPs with end-to-end big data and analytics solutions that are in demand by their customers in the biggest sectors for big data adoption and growth: telecommunications, financial services, manufacturing, and public sector. Our vendor portfolio not only covers the necessary IT platforms and architecture to handle the data center needs for big data but also the diversity in vendor portfolio to provide multiple use case adoption amongst end users.

For more information visit: http://security.techdata.com.

Sources:

IDC, Worldwide Semiannual Big Data and Analytics Spending Guide;
https://www.idc.com/getdoc.jsp?containerId=IDC_P33195

Business Wire, “Big Data and Business Analytics Revenues Forecast to Reach $150.8 Billion This Year, Led by Banking and Manufacturing Investments, According to IDC”

Bughin, Jacques. Journal of Big Data, (2016, 3:14); p. 16

 

Tags: Big Data, Analytics