10 Ways to Turn Big Data into Big Value

10 Ways to Turn Big Data into Big Value

Big data can generate a lot of value, but only if your organization really knows how to make the most of it.

Currently, it's clear that big data has made its way onto the stage - more than half of the world's enterprises and organizations are already looking at big data projects as an opportunity for future growth, and are planning to further increase their investments in big data projects in the coming years.

But the value of big data doesn't just come from collecting the data, that's just the beginning. The real value of big data comes from your organization's ability to use the stored information to discover new insights and analyze them, and then extract useful value to drive better business decisions and grow your business.

Modern business intelligence solutions today can lower the barriers to entry for big data projects and further enhance the value of big data through user-friendly solutions. This allows more stakeholders within your organization (not just data scientists) to access, analyze, and collaborate on the data your business collects.

How do your organization's teams capture the driving value of big data?

Big data can provide your company with more detailed insights into key elements of every aspect of your organization to drive better, more confident, data-driven business decisions.

It fosters an entrepreneurial culture that encourages employees to test and validate their ideas through data analysis.

By making this big data information accessible to everyone involved, the ideas that will drive the next big, creative change in your business can come from any employee in your organization - not just data scientists.

What exactly is big data?

Big data is data that is so large or complex that the average business organization has difficulty managing it using standard databases and software tools. But because every company has different capabilities and requirements, "big data" is a relatively subjective term - what is "big" to one organization is "big" to another. What is "big data" for one organization may be "average" data for another.

Want to get more value from your organization's big data investment program?

Here are 10 ways to help your organization get more value from its big data analytics program:

Choose the right way to access big data.

The ability to gain better insights for analytics is related to the information about the data your organization collects.

Giving the entire business organization access to big data.

Make it easy for relevant users to find the data information they need.

Driving collaboration across departments within the organization to drive innovation.

Build a flexible and agile analytics environment in order to meet the needs of each user.

Ensure that the analytics solutions used by the organization are easily accessible to relevant employees from anywhere, on any device.

Deploy a scalable solution to ensure that it can evolve with the changing business needs of the organization.

Ensure that your organization's business intelligence solution can easily adapt to future technologies.

Choose a BI solution with a broad partner ecosystem.

I. Choosing the right approach to accessing big data

When it comes to how to access and analyze all that data information, there's no one set of methods that's set in stone -- after all, every different enterprise organization will have different needs, different use cases, and different infrastructure configurations.

The approach, or combination of approaches, that your organization chooses will depend on the actual needs of the particular users it needs to satisfy, weighed against the tradeoffs you're willing to accept.

Related questions to consider when choosing an access method for Big Data in your enterprise organization:

How much data does your enterprise need to support? Millions? Or billions?

Will relevant non-technical users need access to your organization's data, or will only IT and data specialists have access to it? Will your organization only run data analytics on the entire data set? Or does your organization want to be able to analyze a selection of related data?

Does your organization need to provide a smooth, highly interactive experience for end users? Is flexibility or user performance paramount to your business?

Second, the ability to gain insights and analytics is more about how you collect the relevant data

Previously, the biggest challenge for your Big Data program was probably identifying and collecting the information your business really needed from a wide range of data sources.

And today, that part is easier than ever. What really matters now is whether your organization can collect and integrate all of this data -- no matter where it comes from or how it's formatted -- and ultimately discover all of the possible connections among all of the relevant data.

In order to gain a more comprehensive view of big data, organizations need to adopt a BI solution with a correlation model so that your organization can navigate through all the connections in all the data. This way, your organization's users will always have access to a complete view of your business so they can make better, more informed decisions.

Unlike traditional data models, which limit what data you can see, how that data is connected, and what queries you can perform, a correlation model identifies all the relationships between all the data in your organization. This allows every user -- not just data scientists -- to quickly and easily explore the right data for their needs and use interactive selection and keyword search to uncover unexpected key and insightful insights.

Three: Make big data accessible across the entire organization

When the idea of big data first emerged, only a handful of people -- primarily data scientists and analysts -- realized its enormous potential. Non-specialists simply didn't have the knowledge, tools, or experience needed to explore and use data in a meaningful way.

And today, that's gone. Now, your organization must put big data in the hands of users in your business units. After all, only those closest to your business really know what valuable questions to ask; and what analytic insights driven by data will have the greatest impact on your business.

The right self-service business intelligence solution can help your customers in this regard by giving business users smooth access to the data they need, while keeping data governance and management in the hands of your organization's IT team. With self-service BI solutions, business users can use interactive visual dashboards to freely explore data and find answers to questions without relying on IT, improve business processes, and drive innovation across the organization.

Factors driving the shift toward self-service analytics:

In a recent report, Forbes Insights surveyed 449 senior IT and business professionals about why they decided to move to a self-service model:

62 percent of respondents want more open access to data.

76% wanted more timely data analysis.

71% of respondents want higher quality data and analytics.

Four: Make it easy for users to find the big data information they need

More and more enterprise business managers want hard evidence to support their business decision-making process. Unfortunately, however, these users are often inexperienced at finding the answers they need in a large, growing repository of data.

To help business unit users find these answers and get more out of big data, your organization needs to make it easy for them to explore big data.

Your organization can do this by providing a BI solution that:

Allows business unit users to intuitively access the data they need without relying on IT to run queries and generate reports.

And provides natural language search capabilities to make it easy to find the information they need.

Discover connections and relationships between data from different sources - even unrelated data in unexpected ways.

Visualize and visualize data in a clear and concise way.

What is natural language search and how can it help organizations?

With natural language search, users can perform queries in regular spoken language. This is extremely useful for users who lack specialized knowledge of data and may not know the technical terminology required to find accurate information in a database. BI solutions that include this feature enable more users (not just data scientists) to gain insightful analytics from an organization's big data.

V. Fostering collaboration across enterprise departments to drive innovation

What good is a great discovery if it can't be ****enjoyed? If the people involved within your organization can't share their insights with a wider range of colleagues, then your organization is undoubtedly missing out on the best opportunity to drive inter-departmental collaboration, and it's not conducive to further expanding on these good initial idea concepts and making them better. Even worse, if other colleagues haven't heard about your findings, they may end up repeating similar data explorations, which in turn can lead to a decline in business productivity.

But it's not enough to just share data; your organization must share it the right way.

Consider an "enterprise-ready" BI solution that offers the freedom of self-service analytics (allowing each user to explore and **** with the data as they see fit), while also providing the organization with comprehensive governance capabilities (controlling who has access to what data information, so every employee is able to work based on a single source of truth).

By striking a balance between self-service and big data management, your business can leverage the collective intelligence of your entire enterprise organization, combining the expertise of multiple teams and individuals to disseminate new ideas and concepts, foster discussion, and drive innovation.

Ensure that your BI solution is properly managed:

Effective data governance ensures that access to analytics and big data is properly controlled and managed across the organization.

If the proper level of big data governance is lacking, errors, variations, and redundancies can occur, making it difficult for users to validate what's really going on in the data, leading to delays and disruptions.

The right big data governance can help your organization avoid these inconsistencies and ensure that every employee is able to get the insightful analysis they need from the same trusted data.

Six: Build a flexible and agile analytics environment that actually meets the needs of each user

Keeping up with the vast amount of new information that big data provides is no small challenge. The onslaught of big data can make it difficult for business users to really dig deep, explore and get the answers they need in a timely manner.

To stay afloat, your organization should consider creating a flexible and agile analytics environment where your IT team can quickly and incrementally build BI solutions that respond to the changing needs of business users.

For example, your organization may need to evolve from guided analytics to self-service BI as users become more familiar with the data.

This allows them to explore more big data on their own and drill down into the details more quickly. Using a flexible framework, your organization can easily meet the needs of these users without significant cost or development time.

VII. Ensure that users can access analytics solutions anytime, anywhere, on any device

With the increasing computing power of cell phones, tablets, and laptops, enterprise employees are increasingly conducting business outside the office.

Whether it's on a train, in an airport terminal or in a client meeting, today's enterprise business teams want to be able to access their work materials whenever their business needs them.

To meet these demands, your organization needs to be able to deliver analytics solutions to your customers and users in a variety of formats - ensuring that their expectations for the full range of functionality they need are met wherever and whenever they need it.

In addition to providing direct access to analytics solutions through cloud-based services or online portals, another way to ensure that users have smooth access from anywhere is to use open APIs in your organization's embedded analytics applications. access the information they need, whenever they need it.

Self-service BI brings the power of analytics to the masses, but for some users, getting additional applications can be a real challenge. That's why some products and organizations embed analytics directly into familiar environments or applications that users use every day.

VIII. Deploying and implementing scalable solutions that evolve with the business needs of the organization

Often, the amount of big data that an organization collects is only going to get bigger. But no matter how the data repository scales, your users want a smooth access experience without having to wait long periods of time or experience outages. As data sets continue to grow, most tools struggle to keep up with this demand.

To ensure that users can continue to explore data the way they want to, adopt an on-demand scalable BI platform that delivers outstanding performance even as the volume of data grows and applications become more complex. The platform should employ a variety of tools and approaches so that your organization can maintain an interactive and dynamic experience for end users, regardless of how much data your organization generates.

In addition, look for a business intelligence solution that uses in-memory processing to perform on-the-fly calculations.

These solutions can process and answer questions at the "speed of thought," allowing users to keep digging and exploring. This, in turn, drives a culture of innovation and discovery throughout the organization.

What is in-memory processing and how can it help organizations:

An in-memory database is a data processing technology that temporarily stores and computes information in random access memory (RAM) without having to retrieve data from disk storage each time a user makes a new selection or calculation. Data can be read and analyzed more quickly in RAM, making reporting (and decision making) faster than with more traditional methods.

9. Ensure your organization's BI solution can easily adapt to future technologies

The technologies for managing and exploring big data are rapidly changing to provide better, faster solutions for today's enterprise customers, and in turn, insightful analytics from big data. But integrating the latest technologies into existing analytics platforms can be challenging and sometimes impossible. So organizations should ensure that the analytics solutions you employ can quickly and easily integrate with new technologies.

Open APIs, for example, can bring new capabilities to your organization's existing solutions as easily as adding a few lines of code. It's also important to have online communities focused on custom development. From there, developers can ensure that your product or solution stays up to date with the latest technological advances by easily collaborating with others.

What is an open API?

An open API is a public interface that developers can use to integrate third-party solutions into their own. In essence, an open API controls how easily two different applications can communicate and interact with each other. BI solutions that offer open APIs enable organizations to easily plug in multiple solutions to perform specific functions that are not possible with standalone solutions.

X. Choose a business intelligence solution with a broad partner ecosystem

When it comes to big data projects, sometimes organizations need a little extra help to see the overall picture. When choosing a business intelligence solution, it's imperative that organizations look for vendors that can maintain partnerships with a large number of multiple technologies.

This will help streamline data interactions and ensure that all of your organization's BI solutions are working efficiently. Additionally, having enough partners can always provide the most appropriate solution for your organization's business needs - now and in the future.

What types of technology partners should your organization choose?

Data storage and management solution providers store and query your organization's data and provide the infrastructure needed to run analytics solutions.

Data wrangling solution providers distill raw data and reshape it into usable data sets.

Machine learning solution providers automate analytical model building by using algorithms that learn iteratively from data.

Big Data, Big Potential

Big data has the potential to transform your organization's business, but in order to really get real value out of your company's big data program, your organization needs to know how to make the most of it.

The right business intelligence solution can help your organization maximize the return on your big data investment by:

Providing a complete view of your business and the external factors that affect it.

Driving better data-driven decisions in every area of your business.

Enable more business users to access and explore big data anytime, anywhere.

Foster a culture of collaboration, proactive exploration and innovation throughout your organization.

Enabling scale as the business grows to meet future needs.