by Analytics Insight
January 21, 2022
Lumenore delivers organizational intelligence by sifting data from any business application
Organizational intelligence (OI) is the capability of an organization to comprehend and create knowledge relevant to its purpose. In other words, it is the intellectual capacity of the entire organization. Lumenore is a powerful, intuitive, and cloud-based BI and analytics platform that delivers organizational intelligence by sifting data from any business application. Analytics Insight has engaged in an exclusive interview with Naren Vijay, EVP of Lumenore.
1. Kindly brief us about the company, its specialization, and the services that your company offers.
Lumenore is a powerful, intuitive, and cloud-based BI and analytics platform that delivers organizational intelligence by sifting data from any business application. It is the flagship product of its parent company – Netlink, which is a value-added technology and business solutions, provider.
We started our journey amidst the explosion of data taking place across industries and are known to deliver organizational intelligence by decoding data from any business application. Our self-service business intelligence with no-code analytics helps businesses collaborate with the entire team to derive faster and simpler insights to drive business growth. We specialize in driving business growth and team productivity with the help of actionable insights. Lumenore delivers a seamless experience to the entire team which helps them to derive insights from raw data and have a transparent view of its operations.
Lumenore is known for its AI-driven recommendations and conversational analytics. One of our biggest USPs is that we provide a user-friendly no-code environment to the team across the organization. This ecosystem can be used in multiple projects like interactive visualizations, conversational querying, or streamlining organizational decision-making with future-ready business intelligence.
Known in the industry for providing cost-effective analytics and providing targeted value through actionable insights, our services include end-to-end data solutions, advanced data discovery, natural language querying, and a suite of analytics solutions to drive business growth.
2. With what mission and objectives, the company was set up? In short, tell us about your journey since the inception of the company.
The vision of Lumenore is to simplify decision-making at all levels in the organization and make business intelligence actionable.
Lumenore was started in 2013 with a solid belief that technology and analytics should not come at the cost of accessibility. We strongly believed that data literacy shouldn’t become an arms race. Everyone in the organization should have access to the data and at the same time, businesses should not be required to invest heavily in analysts to interpret it. It was our intent to create a powerful tool that was also easy to use.
We are in the business of simplifying insights. Rather than being dependent on a few experts to drive business intelligence, our no-code analytics platform allows the entire team to make decisions based on analytics.
Lumenore is progressing with an objective to power the growth and performance of organizations with a unified BI platform that bridges the distance between data and decisions.
The decade-old saying ‘data is the new oil’ is much more relevant today. In fact, it is expected to be relevant as the industry evolves with time. In today’s scenario, there is still a need to close the loop with data and analytics. Data and business intelligence needs to cover some distance to drive decision-making. As a result, data solutions are expected to be in the driver’s seat for the coming few years. The solutions are expected to provide big data analytics to the organization. But in the end, these analytics and big data need to trigger decision making. Also, an assessment of the decision taken based on data and analytics should be built into the system.
For the future, trends like augmented analytics that provide automated data discovery using machine learning / statistical techniques, narrative insights that provide insights in self-explanatory natural language, and ease of use of analytics platforms are expected to drive the growth of the industry.
4. How is your company helping customers deliver relevant business outcomes through the adoption of the company’s technology innovations?
Lumenore is committed to delivering relevant business analytics to organizations across the world. We are known for our operational analytics that helps in getting a good grip over the day-to-day operations on a real or near real-time basis.
Another technological innovation from Lumenore is pervasive analytics. This is ingrained in our DNA that access to analytics should be available across the organization and not just with a bunch of managers and experts. That is why we are providing solutions that make analytics simpler, faster, and more efficient for everyone in the organization.
The Ask Me and Do you know modules by Lumenore focusing on instant analytics deal with complex implementation and are among the most popular innovations from our stable that has been used by our customers.
5. What are the key trends driving the growth in Big Data analytics/AI?
An estimate suggests that there will be 175 zettabytes of data in the global data sphere by 2025. While data on its own is meaningless, when combined with the right business intelligence solutions, it suddenly becomes a goldmine of insights. Self-service-driven analytics can become the game-changer in this regard as it empowers every user to navigate their own way through the data and seek the analysis they want. Moreover, self-service-driven advanced analytics will allow users to focus only on the outcome by removing the complexity of machine learning jargon.
Another trend that is driving the growth in this segment is the increasing use of cloud-based technologies. Many businesses have started to realize that big data analytics require horizontally scalable infrastructure. Businesses have started to prefer analytics platforms that are Cloud or SaaS-based.
There is also a growing realization that analytics should be performed on the complete data set and not on the specific parts. This has led to companies leveraging a data universe that comprises data management architectures such as data engineering, data lake, data security, etc. There is also a growing trend to make data accessible to all levels of the organization and not be in the hands of a limited few.
We believe that these trends will continue to drive the growth in this domain, and will also push companies to increase their BI/big data budget.
6. What does your technology and business roadmap look for the rest of the year?
Lumenore’s technology and business roadmap for the rest of the year is geared towards enabling any and all business users to become self-sustainable through the adoption of business analytics such that they have a minimal need of IT, if at all. From a business perspective, we are also looking at expanding our customer portfolio this year and have chalked out plans to onboard more than 100 customers with $4.5 million annual recurring revenue (ARR).
7. What is the reason that organizations are using Big Data Analytics?
Most organizations have now become aware that Big Data Analytics is a game-changer and disruptor. By using Big Data Analytics, organizations can track operational excellence with a transparent view, and predict future gains and downfalls. In addition, Big Data Analytics allows businesses to identify and mitigate potential risks, and employ custom industry and business-specific solutions. Overall, the reason that organizations are using Big Data Analytics is to improve their actionable decision-making with the use of data-driven conclusions.
8. The industry is seeing the rising importance of Big Data Analytics and AI. How do you see these emerging technologies impact the business sector?
Emerging technologies such as Big Data Analytics and AI have been making their presence felt for years. However, the pandemic has, in many ways, acted as a catalyst. In this line of business, the pandemic has led to two radical shifts—it has sped up digital transformation across industries and sectors which means that we now have even more data than anticipated, and it has made consumer behaviour harder to predict. To respond intelligently to these shifts, the business sector needs AI and Predictive Analytics.
Predictive Analytics, in particular, is gearing up to become one of the biggest trends of 2022. From seasonal trends to demand forecasts, Predictive Analytics can deliver intelligence that is critical to decision-making and help guide businesses to making better decisions in real-time.
With AI at the helm, organizations can simplify analytics and business intelligence for everyone in the organization, irrespective of the technical skills they have. For instance, one important application of AI is conversational querying whereby users can ask for business insights in natural language, like Googling information, and get those insights from their BI platform
This way insight can be accessed by anyone and drive growth at all levels, and not just in the realm of the decision-making executives at the top of the management hierarchy.
9. How can businesses efficiently extract the value from data, without increasing cost and complexity?
This is a two-part problem that needs to be dealt with so that businesses can efficiently extract value from data.
Increasing complexity comes from the exponential growth in streams of data. To decrease this complexity and continue extracting value from data, businesses need to focus on engineering a robust data universe that ingests data from various sources, rapidly transforms it, and delivers an agile, streamlined warehouse that can, in turn, derive value from data faster.
Increasing cost is the by-product of facing a lack of employees with sufficient data literacy and technical skills. To control costs, businesses need to ensure that insight is easily accessible by anyone in the organization, irrespective of their levels of data literacy. Be it through conversational querying, where users can just ask for insights in natural language, or through advanced data discovery, which allows users to access augmented analytics in an easy-to-understand way with just one click, ensuring the accessibility of insights determines the effective usage of the insights.