How to Unlock Big Data Value

There is hardly any resource that is more important to the strategy and success of a business than data. With simple inferences drawn from this data, such as what kind of products a part of consumers buy, firms can tune their approach for better business decisions. But there is data, and there is big data!

Improvements in computing have resulted in an increase in the data available to companies. There has been an explosion in the amount of data that is generated every day. While spreadsheets and nicely coded files allow companies to keep a realistic amount of data, the computing ability to gather, store and consolidate data on a large scale meant that information could be available at the click of a button.

What is Big Data?

What is Big Data

The concept of Big Data is not new. It dates back to 2000, where it was described in terms of its huge volume, the extremely high velocity with which it is created and the diversity of sources that create and share this data.

The variety of data comes in two categories: structured, and unstructured. Structured means that the data is carefully labeled and categorized. For example, it could be high amounts of data showing how many Google users search a particular term in a day.

On the other hand, unstructured data is data that is documented without much intent or purpose. It is often recorded without being in any dynamic use. Such data is therefore, not neatly tagged or categorized. This type comes in a number of varieties—text, video, and images. Unstructured data is random, enormous and difficult to analyze.

The volume of Big Data overwhelms the normal data warehouse. For instance, Facebook reports that its users register 2.7 billion comments and likes per day. For many, this extent of data is nerve-racking—they cannot keep up with it, sort it, analyze it and extract value from it.

It can be challenging to manage data when it flows at a velocity that many players cannot handle. For Big Data to be a useful, it must be analyzed at a rate that matches the intense speed at which information enters data warehouses.

The idea behind Big Data and any type of data is: the more you know, the more you can do. Simply put, information is power and in the modern world we are in, power is dynamically measured by how much one knows and can act on. By gaining access to growing amounts of data and relating more data points, it is possible to identify connections that were previously concealed and harness powerful insights from them.

Big Data projects use quality analytics that influence machine learning and artificial intelligence to hitch the potential insights. The process of tapping the value in this data is done in three steps:

• Sourcing data

The first step is sourcing data from several applications and places. Basically, traditional means of data integration cannot handle this amount of data which are normally in hundreds of terabytes.

• Create customized solution for managing and working with the data

In this step, firms can decide whether to store the data on premises or in the cloud. Many companies prefer the cloud option since they can easily regulate resources to utilize only what they need at that time.

• Data Analysis

It is during this step that companies can unlock the clarity and insights they need to expand their business.

How Big Data Expands Business Analytics Capabilities?

The business intent for organization has remained unchanged—to help businesses monitor, manage, diagnose, predict and optimize performance in all areas of a business. To date, analytics has been largely used to in-house generated, highly structured business data.

Big Data represents improvements in technology and capabilities that make analyzing big amounts and unique data types both affordable and feasible for a broad range of uses. Specifically, Big Data fuels business analytics with three unique benefits:

• Improves processes and performance
• Delivers more complete answers and new insights
• Creates new business models and differentiated services

How Big Data Expands Business Analytics Capabilities

1. Improves Processes and Performance

Equipped with more complete answers and insights, businesses can look to reorganize processes and measure performance advances in new ways. Achieving operational efficiencies can save costs, reduce financial losses and litigation risks, improve customer satisfaction and improve product quality.

2. Delivers more Complete Answers and New Insights

In the past, the cost of retaining data needed to be weighed against the value it provided to the firm. Data with known usefulness was typically summarized in data warehouses. The source data was maintained for long periods and then deleted or archived. Asking a new business questions became hard since the source data may be no longer available, if it was retained in the first place. Data that was difficult to analyze or one with uncertain value, such as video feeds or log files was typically deleted on a weekly or daily basis.

With advancements in technology such as columnar data stores, Hadoop, and Massively parallel processing systems, storing and processing of huge amounts of data has become easy and at a fair cost. Storing more data allows organizations to:

• Analyze data over long periods of time, which enables them to identify trends and exclude anomalies.
• Keep all available properties which could identify new casual relationships.
• Include larger sample sizes which shrinks the effect of wrong data and increases the confidence factor.

3. Creates New Business Models and Differentiated Services

Future thinking finance professionals are partnering with business experts to assess new sources of income and business model invention from big data assets.

Here are some types of data that are prompting new services

• Global Positioning System (GPS), telemeter and other sensor data: vehicle manufactures using telemetry data for diagnostics can influence those signals to create an intelligent on-board concierge system as a new service.
• External data combined with an internal source: agencies in the travel industry are exploring methods to cross-reference weather data with travel plans.
• Customer Contact Information: financial bodies such as banks and credit card companies with access to customer information and vendor purchases can experiment by offering customers with promotions paid by vendors. For instance, a coffee bought using a credit or debit card prompts the financial entity to sending to a vendor offer such as a 10% for a second cup to the customer’s email or phone.
• Click-through Data: on-demand engagement marketing providers can analyze emails to offer customers with guidance on the best dates and times to send emails for maximum response. Focusing a customer email campaign can increase performance thus boosting the value of the service.

What are the User Cases for Big Data?

Business can use Big Data in their daily routine to help them expand their organization capabilities. There are a number of areas that businesses can benefit from using Big Data. Here are a few cases:

What are the User Cases for Big Data

1. Revenue Assurance

Using data, organizations could improve identification and stop fraud before it can occur. Industries experiencing high levels of fraud such as healthcare would mostly benefit from this.

2. Customer Lifecycle

Organizations can avoid instances of consumer frustration and provide a fast response. This way, they can improve consumer experience. This is most likely to benefit service-based industries.

3. Risk Mitigation

Each day, networks carry petabytes of sensitive data for businesses, consumers, and governments, opening an ever advancing threat of invasions and security attacks. Data confederation across wider geographic and network footprints would allow suspicious patterns to be identified while signing the need for speedy action.

4. Market Execution

Big Data allows for better market services via analytics and creation of improved opportunities for up-selling and cross-selling. Online business and Banking are the most potential beneficiaries.

5. Advanced Advertising

The more enterprises learn about customer behavior, the easier it becomes to change that info back into advertising. With advanced data-based targeting, the effectiveness of adverts doubles. Cost-per-thousands of over 50% become possible. To further benefit through the Big Data analytics, there is need for the trust mechanisms to lessen privacy restrictions and make sure that targeted ads are in line with the consumer information across the network.

6. Operations Management

Big Data could help almost any organization operate better and more efficiently. A service provider could improve the daily operations of its network. Retailers could create more effective and profitable point of-sale interactions. And nearly any supply chain would operate more efficiently.

7. Product Innovation

Consumer input is critical in product development, and many companies are currently demanding to know more about their customers’ likes and dislikes. Integrating non-company sources of data such as social-network feeds would offer a more complete view of how consumers feel about a product. This could potentially reveal the need for a new product before it is imagined or on the creation board.

8. Pricing Models

New pricing procedures will create innovative monetization opportunities and more efficient interactions with consumers. This could particularly be beneficial to retailers in terms of pricing models that are tied to the behavior and location of consumers.

Conclusion

Businesses can unlock so much value from the Big Data. They can benefit greatly from this data in several areas of their operations. This data opens new insights¸ improves processes as well as opens an opportunity to develop new business models. Different businesses from different industries can all benefit from Big Data.