• Data Product: Improved Decision-Making Capability

    Data products can help organisations make better decisions by providing accurate, timely, and actionable insights. By analysing large amounts of data, organisations can identify patterns, trends, and anomalies that might not be apparent otherwise. This can lead to more informed decisions that are based on data-driven insights rather than intuition or guesswork.

  • Data Product: Increased Efficiency and Productivity

    Developing data products can also help organisations become more efficient and productive. By automating certain tasks and processes, data products can reduce the amount of time and resources required to complete them. This can free up employees to focus on higher-value activities, such as developing new products or services or engaging with customers.

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Data: Li - Next-Gen Data Governance

Introducing our new next-gen data governance product that is set to transform data governance practices and align with the future of the digital enterprise in the digital decade.

Our product is designed to create a data-driven decision-making process that increases efficiency and productivity across your entire organisation. It takes a holistic approach to data governance, incorporating cutting-edge technologies and best practices to provide a comprehensive solution that can meet the needs of any organization. With AI powered advanced data governance capabilities and real-time insights, our product enables you to make informed decisions that are based on accurate and timely information. Whether you're in finance, marketing, or operations, our data governance product will help you streamline processes, eliminate redundant processes, and reduce errors, paving the way for a more agile and competitive organisation. 


Data: Li - Purpose and Benefits

With Data: Li, organizations can establish a strong and data-driven data governance framework that aligns with industry standards and regulations. This helps to ensure that the organisation is compliant with data protection laws and regulations, while also minimizing the risk of data breaches and privacy risk.

Data: Li is a term that is inspired by the words "metadata" and "analytics." It refers to the process of analysing and managing metadata to gain insights into an organization's data assets. Metadata is information about data that describes its characteristics, such as its format, structure, and content. By analysing their own organisational data and metadata, organizations can gain a deeper understanding of their overall business objectives, which can help them make better decisions and drive efficiencies in the organisation.

By combining metadata and analytics, organisations can gain a holistic view of their data, usage, and performance. This can help them to identify opportunities for improvement, optimise their data management processes, and ensure that their data is accurate, secure, and compliant with industry standards and regulations.

Data: Li - Next -Gen Data Governance tool is build with the above in mind and provides an intersection of metadata and analytics, and it runs on the importance of these two concepts in modern data governance and management:

Purpose:

  • To create digitalisation for data management policies.

  • To manage metadata effectively to gain insights into an organisation's data assets.

  • To facilitate data-driven decision making across the organisation.

  • To establish a strong data governance framework that aligns with industry standards and regulations.

  • To reduce manual effort, minimise errors and increase efficiency by providing automated data governance & management capabilities.

  • To scale data knowledge and literacy an organisation's data.

Benefits:

  • Improved efficiency in managing all digital data policies.

  • Improved data management capabilities.

  • Increased efficiency and productivity.

  • Facilitates compliance with data protection laws and other regulations.

  • Provides real-time monitoring and alerts to keep data stewards and data owners informed about any changes in data quality or security.

  • Enables organizations to identify opportunities for improvement and optimise their data management processes focusing on eliminating manual efforts.

  • Provides a holistic view of an organisation's data, including its usage and performance, which can help to inform decision-making across the organisation and future planning.