UNLEASHING THE POWER OF DATA

Eranda Adikari, Product Head of Data Insight at Dialog Enterprise, highlights the importance of data insights for businesses. He emphasizes that effective analytics management can drive revenue gains of 10 to 12% for enterprise-level organizations, and how understanding various analytics types and leveraging data throughout the value chain can help businesses extract value and gain actionable insights.

Diagnostic analytics identifies root causes of failures, enabling data-driven corrective actions, while AI and machine learning foster predictive and prescriptive analytics for enhanced performance. Eranda’s insights shed light on how businesses can thrive by harnessing these approaches.

Can you explain how Dialog Enterprise’s data insights services help businesses convert large and complex volumes of data into valuable business insights?

With a strong background in Dialog and extensive experience in analytics, we invest in advanced technologies, like AI, and continuously develop our people. We also possess established infrastructures like data warehouses, data lakes, and data visualization tools that can help businesses make the most of their data.

As pioneers in Sri Lanka’s analytics industry for the past two decades, we help corporate clients derive value from analytics and establish cost-effective infrastructures. Our services include conducting maturity assessments using the TDWI framework to analyse levels and create an analytics roadmap tailored to each organization’s unique maturity and culture. We assist with requirements gathering, technical architecture, and deployment. Additionally, we prioritize cultural aspects by conducting awareness sessions and training programmes for technical staff and executives. We provide valuable insights based on customer data while prioritizing data privacy. Our expertise extends to system and application deployment, assisting organizations with analytics implementation, cultural adaptation, and data-driven decision-making, such as identifying optimal locations for outlet expansions.

How does Dialog Enterprise’s API integrate crowd analytics, data as a service, and business insights to ensure data privacy and comply with international data protection laws?

Data sharing involves two aspects. Firstly, with customer consent, we share information, including customer-level data, under data protection laws. Doing so is legally accepted when customers permit organizations to share personal information with third parties.

Data sharing involves two aspects. Firstly, with customer consent, we share information, including customer-level data, under data protection laws. Doing so is legally accepted when customers permit organizations to share personal information with third parties.

The second area involves crowd analytics and market insights portals, which aim to understand people’s movement patterns. In this case, we strictly use non-PII (Personally Identifiable Information) data for all queries to ensure that no customer-specific information is shared – the process relies solely on aggregated and anonymized data. We adhere to all relevant laws, including those in Sri Lanka. Moreover, telecommunications operators, even in countries governed by the General Data Protection Regulation (GDPR), have engaged in this business for around four to five years.

Could you elaborate on how Dialog Enterprise’s Consultancies-Maturity Assessment service helps organizations enhance data management and leverage new technologies like machine learning and AI?

Dialog Enterprise’s Consultancies-Maturity Assessment service helps organizations improve data management and leverage cutting-edge technologies like machine learning and AI. Analytics projects often face lower success rates when compared to IT projects globally, with analytics projects achieving only about 30% success. To address this, Dialog assesses organizations across dimensions such as organization, resources, analytics, governance, and infrastructure. This comprehensive approach recognizes that deploying a solution solely focused on technical aspects can lead to failures if businesses do not consider other critical attributes like resource skills and organizational culture.

The maturity model ensures that culture, governance frameworks, and infrastructure are integrated into the solution deployment process, offering a 360-degree view for increased project success. Even individuals without an IT background can understand and appreciate this approach, shedding light on the reasons behind the failure of many analytics projects. By embracing a holistic perspective, organizations can drive their projects towards success.

Dialog Enterprise has started a Data Science Academy; can you tell us more about this?

We established the Data Science Academy in response to the lack of industrial or corporate-level training in Sri Lanka. While online platforms like Coursera, Udemy, and LinkedIn offer alternatives, we recognized the demand for instructor-led training from organizations.

Our academy focuses on three levels: technical, business, and C-level, and we have developed extensive content in these areas. Our strong partner network of experts from various industries, including Sri Lankan professionals working abroad and university lecturers with deep industry connections and expertise, enable us to offer tailored training programmes relevant and up-to-date with the latest technological advancements. Over the past year, we have successfully conducted more than 50 programmes, benefiting over 1,000 participants from over 35 corporations, as evidenced by the positive feedback we receive.