How to Lower Entry Barriers To Make Analytics More Accessible and Powerful

In 2011, Bloomberg Businessweek Research Services posed a question – “Is business analytics overrated?” This query sounded utterly plausible at that time, considering only one in four organizations supported business analytics to help realize tangible benefits.

Well, time flies, and very swiftly indeed when technological evolution powers data’s case. At present, analytics is known to make the decision-making process 5x faster, prospect conversion 23x more likely, and average ROI about 1300% higher.

So, when businesses claim that data analytics is one of the most critical competencies driving business intelligence (BI), the stage is set for a data-driven economy that demands leveraging the power of analytics for survival as well as growth.

That said, to make the spread of analytics even wider, it’s necessary to lower the entry barriers. Amidst ever-increasing competition, entering this paradigm is challenging, while it needn’t be so.

Often businesses are plagued by internal barriers, including deficient expertise, weak understanding, and fragmented operations for data gathering and management. External barriers like data availability, investment, etc., further make it challenging to realize the case for analytics befitting the vision of growth.

All things considered, the adoption of go-to technologies and adherence to certain practices can undoubtedly help businesses lower entry barriers and sustain growth based on advanced analytics.

Technologies That Lower Entry Barriers and Power Analytics

1. Cloud – The Basis for Business Intelligence

Today, businesses are increasingly becoming data-driven by leveraging the cloud. With the speed of data generation increasing multi-fold, the need for the cloud is clear. In fact, as per Harvard Business Review, more than 87% of the c-suite executives believe the cloud to be a “critical component” in driving business towards “sustainability goals.”

After all, besides scalability, cloud:

• a. Offers unlimited storage capacity and elasticity to seamlessly analyze complex datasets without increasing investments in infrastructure.
• b. Reduces internal or external barriers, thanks to the simplicity of SaaS (Software-as-a- Service) solutions. With this, businesses can effortlessly scale up their data analytics without worrying about on-premises limitations due to under-resourced resources.
• c. Provides fast and consistent delivery of data-based results to guide decision-making seamlessly all complemented by the manifold spectrum of analytics.
• d. Offers a secure, easy, and intuitive interface technologies and readily tap into big data insights. allowing one to embrace the latest
• e. Can be deployed across all kinds of devices, making it more accessible, thus catering to organizations that are not tech-savvy.

The Case in Point – IBM Cloud Pak for Data and Unparalleled Analytics

An analytics platform and so much more, Cloud Pak for Data lays the foundation for different organizational entities (data scientists and analysts) to reduce departmental fragmentation by collaborating to catalogue, analyze, and administer data and subsequent decisions.

From data unification to virtualization, Cloud Pak works to extract valuable insights from otherwise massively disoriented data sources. Moreover, it provides users with the ability to independently scale their data analytics endeavors.

What makes the solution all-inclusive is IBM’s integration of 45+ tools and templates (including those from third-party developers). For example, IBM Planning Analytics can prominently work in cohesion with Cloud Pak for Data, providing businesses with the ability to plan, budget, and forecast alongside core analytics.

The facility to further integrate Watson Studio, Watson Machine Learning, Watson OpenScale, and IBM SPSS® Modeler makes Cloud Pak for Data a win-win resource for businesses looking to scale beyond the conventional market paradigm.

To add to that, the inherent cloud capability makes the tech easy to adopt, deploy, and
use.

2. Artificial Intelligence – The Present and Future of Data Analytics

Businesses are aware of the potential of AI in automating tasks to get insight-driven results. But only 43% of businesses have a clear strategy defined for using AI.

However, it’s noteworthy that these companies understand the business value linked with Al initiatives. They realize the potential to become almost twice as likely to realize customized curriculums for consumers, make successful investment decisions, optimally use the computing and human resources at their disposal, and report improved financial performance.

All the above is made possible because AI:

• a. Eliminates inefficiencies via the automation of tasks while complementing human intellect with its ability to learn, analyze, and conceptualize events.
• b. Offers the ability to leverage the power of data for making more accurate, insightful decisions with tremendous speed and accuracy to scale actions.
• c. Drives toward a better world by enabling businesses to access a wealth of data, for example, accelerate the discovery of promising areas of growth and best-in-class customer experiences.
• d. Can readily perform tasks data visualization, i.e., organizing the data into meaningful views and packaging the data into sharable reports and dashboards for the stakeholders.The Case in Point – IBM Watson Studio for Data Refinery and Decision-Optimization

An analytics initiative is useless if it doesn’t deliver on its promise to optimize decision-making and eliminate knee-jerk responses.

What you need is a platform powered by “AutoAI” and visual tooling to help extrapolate data and bring predictive and prescriptive analytics into the picture. IBM Watson Studio is precisely such a platform wherein businesses can gain significant value from AI thanks to custom model development for rapid data experimentation, guided by a cognitive agent, and accompanied by intelligent visualizations.

The good thing is that this solution can be integrated with the Cloud Pak platform to augment AI with the power of traditional BI.

Lower the Entry Barriers to Advanced Analytics

At Veracitiz, we believe that no business can be truly agile unless it is data-driven. Given a paradigm shift in how businesses conduct analysis, there is a growing need to manage the time it takes to make decisions and meet business objectives.

That said, the best way to keep your business on the cutting-edge of innovation is to find the most suitable solutions by expanding your collaboration with the experts.