One of the most stressful jobs for analysts is identifying and choosing the right use case for big data as it has the potential to drive high-level business value.
The pace at which digital data is increasing is unbelievable. It is expected that, by 2022, data generated for every human will amount to 2.5 megabytes approximately. In the realm of digitization, industries worldwide are actively collecting tons and tons of data from various sources with the aim to deliver the best product to their customers. But analyzing and managing big data manually is practically impossible. Here’s where the picture of big data analytics comes in. The primary purpose of big data analytics is to identify hidden patterns and correlations, to extract value in an otherwise ordinary looking data. Big data analytics help companies create new opportunities and improve their existing business workflows altogether. This, in turn, help companies to conduct their business better, thereby meeting their organizational goals with high efficiency and accuracy. But, the first and foremost step after the collection of big data is choosing the right use case that can showcase its power.
Why Choosing the Right Use Case for Big Data is Important?
From manufacturing to retail to travel, every industry collects a large volume of digital assets with the aim to enhance their efficiency. With the help of big data analytics, industries can analyze and provide meaning to the gathered data, which can then help shape business decisions. Big data helps analyze market opportunities and also understand customer behavioral patterns and other critics to business parameters.
However, without the right use case, how will you leverage data analytics? Out of the vast amounts of data gathered, it is difficult for analysts and other business leaders to identify the right business use case for their business. But once the use cases have been identified, an organization can then bring life to the data, thereby boosting organizational growth, accuracy, productivity, and efficiency. Therefore, the first step towards getting the desired business outcomes is identifying the right big data use cases.
Which Approach Should Analysts Follow?
Here are few steps that business analysts and leaders should follow in order to choose the right business use case:
- Understanding the business objectives before identifying the business use cases
- Listing down all the business use case categories by predicting and the respective business outcomes
- Identifying big data use case from the listed categories
- Expanding the team of IT experts to better identify the use cases
- Keeping a regular check for new business use cases from the data that pours in real-time
By now you know that the bridge that connects digital data and advanced technologies is a business use case. Hence, with a team of highly-skilled professionals and analysts, you should identify the right use cases by following the approach mentioned above, thereby breaking the data silos for enhanced business outcomes.
Micro Focus’ CyberRes teams up with Google Cloud
Duncan is an award-winning editor with more than 20 years experience in journalism. Having launched his tech journalism career as editor of Arabian Computer News in Dubai, he has since edited an array of tech and digital marketing publications, including Computer Business Review, TechWeekEurope, Figaro Digital, Digit and Marketing Gazette.
CyberRes, a Micro Focus line of business, has partnered with Google Cloud to support the upcoming release of BigQuery remote functions.
The partnership will see CyberRes’ end-to-end enterprise data protection solution, Voltage SecureData, integrate with Google’s BigQuery data warehouse to accelerate and expand organisations’ data science initiatives and help companies comply with ever-evolving privacy regulations.
The integration will enable CyberRes Voltage customers to persistently protect data in use, in motion, and at rest in Google BigQuery. The support for remote functions also enables Google Cloud’s BigQuery customers to take advantage of Voltage’s privacy-enabling technologies. Mutual customers can use Voltage’s format-preserving encryption, hashing, and tokenization services within BigQuery in conjunction with Google BigQuery’s native security to address strict privacy compliance controls. Voltage’s cloud-agnostic and consistent data protection allows all customers to safely use regulated data for analytics across hybrid clouds.
Tony de la Lama, VP of product management, CyberRes, said: “The availability of remote functions from BigQuery is an exciting and critical evolution of Google Cloud’s platform for our customers.
“The integration with Voltage SecureData means BigQuery will allow customers to utilise and support the Voltage data-centric protection approach for secure analytics, enabling enterprises to accelerate and expand their data science initiatives with privacy by default.”
BigQuery, Google Cloud’s highly scalable multi-cloud data warehouse, is designed for business agility and allows customers to gain insights with real-time and predictive analytics, access data and securely share insights with ease. This new partnership adds to Voltage SecureData’s deep capabilities in securing analytics across data warehouses, databases and data lakes and enables customers to shift workloads seamlessly and securely to BigQuery.
“Emerging threats and evolving technology needs are at the forefront of challenges in cyber security. By making its Voltage SecureData solution available to Google Cloud customers from within their BigQuery data warehouse, CyberRes is enabling customers with the technologies needed to protect their sensitive data while addressing and adhering to current data privacy regulations,” said Ritika Suri, Director, Technology Partnerships, Google Cloud.
The CyberRes Voltage portfolio helps secure organisations with continuous data discovery, insight, and protection to reduce risk and enable privacy by design. Organisations can work with high-value, sensitive customer data in its protected state to derive business intelligence without the risk of data exposure in Google BigQuery. The data protection technologies in Voltage SecureData provide flexible implementation and data-centric protection for a virtually unlimited number of structured data types in any language, and in any region, with proven performance, reliability, and scalability.
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