Data Product Archives - Sagar Nikam https://sagarnikam.com/tag/data-product/ Connect - Collaborate - Differentiate Sat, 18 Mar 2023 20:13:53 +0000 en-US hourly 1 https://wordpress.org/?v=6.1.4 https://i0.wp.com/sagarnikam.com/wp-content/uploads/2022/03/Sagar-Nikam-Logo-1.png?fit=32%2C32&ssl=1 Data Product Archives - Sagar Nikam https://sagarnikam.com/tag/data-product/ 32 32 214814251 What are the key skills required to become a successful data product manager? https://sagarnikam.com/2023/03/20/what-are-skills-for-data-product-manager/ https://sagarnikam.com/2023/03/20/what-are-skills-for-data-product-manager/#respond Mon, 20 Mar 2023 07:55:00 +0000 https://sagarnikam.com/?p=205 In today’s data-driven business landscape, data product managers are critical to the success of any organization. These professionals are responsible for overseeing the development and management of data products, ensuring that they align with business goals and meet customer needs. But what are the key skills required to become a successful data product manager? Let’s […]

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In today’s data-driven business landscape, data product managers are critical to the success of any organization. These professionals are responsible for overseeing the development and management of data products, ensuring that they align with business goals and meet customer needs. But what are the key skills required to become a successful data product manager? Let’s explore.

Technical Skills

Data product managers need to have a solid understanding of data science concepts and techniques, as well as knowledge of data analytics and visualization tools. They should also be experienced with data management and storage solutions and have familiarity with programming languages such as Python, R, and SQL. A strong technical foundation is essential for a data product manager to effectively manage data products and work with technical teams.

Business Skills

Understanding customer needs and identifying market opportunities are essential for any successful data product manager. Business skills are critical in product development as data product managers need to align data products with business goals. They should be well-versed in business strategy and have strong project management and organization skills. They should also possess excellent communication and interpersonal skills to effectively collaborate with different stakeholders in the organization.

Analytical Skills

Data product managers must be able to analyze and interpret data to make informed decisions. They need to have strong problem-solving and critical thinking skills, and they should be able to identify patterns and trends in data. Experience with A/B testing and experimentation is also important to help data product managers make data-driven decisions.

Leadership Skills

Data product managers must possess strong leadership skills to manage cross-functional teams and effectively manage stakeholders. Experience with agile development methodologies and ability to inspire and motivate team members is important. They must be strong decision-makers and should be able to manage risks effectively.

Conclusion

In conclusion, becoming a successful data product manager requires a combination of technical, business, analytical, and leadership skills. It is important for aspiring data product managers to continuously learn and develop these skills, as the field is constantly evolving. A career in data product management can be fulfilling, challenging, and exciting for those with the right skills and mindset. If you’re interested in pursuing a career in data product management, start by honing your skills in these areas and stay up-to-date with the latest trends and technologies in the field.

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Sharp ‘Data Risk’​ Strategies for Accelerated Digital Transformation https://sagarnikam.com/2022/03/11/data-risk-strategies-for-accelerated-digital-transformation/ Fri, 11 Mar 2022 22:04:11 +0000 https://sagarnikam.com/?p=158 The post Sharp ‘Data Risk’​ Strategies for Accelerated Digital Transformation appeared first on Sagar Nikam.

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Sharp ‘Data Risk’ Strategies for Accelerated Digital Transformation

Sharp 'Data Risk' Strategies

The pandemic may be reshaping corporate digitalization strategies. However, the pandemic has also significantly accelerated digital transformation, as confirmed by 85% of CEO in Fortune/Deloitte CEO Survey Jan’21.

"We are moving slowly into an era where big data is the starting point, not the end."  - Author and digital visionary Pearl Zhu once

One of the challenges is departments, or individual domains have adopted their own processes and standards for accessing and using the data. Lack of centralized broader governance initiatives could cause high data risk as well as duplication of system, multiple data standards, and inability to monetize the data. This could also risk the confidentiality, integrity, and availability of data.

Another challenge is organizing and managing a large amount of unstructured data. It takes significantly more effort as compared to structured data, which is easy to categorize. It is very difficult to quantify the risk related to unstructured data, intern difficult to mitigate.

 Knowing where to start

  •  Governance & Compliance – There should a consistent and organizational level data management practices. Data governance and Compliance need to be in place to ensure the implementation. There should be proper training and communication about the importance of data risk management. All regulatory & Compliance data should be tagged as high importance, like customer data for General Data Protection Regulation (GDPR) or financial firms risk data under BCBS 239.
  •  Data Quality Framework & Data Lifecycle – The data quality framework helps to standardize the data attributes and rules. There are 5 important traits of quality of data: accuracy, completeness, reliability, relevance, and timeliness. Understanding of Data lifecycle helps organizations to mitigate Data Risk at all stages.
  •  Technology Enhancement – Metadata and repositories should have added attributes to store the data classifications and tags. There should be a proper facility to process unstructured data to avoid any data leakage. Technology advancements are important in terms of securing data from external cyber-attacks, which could cause a major financial and reputational impact on the firm.
  •  Process & Data Ownership – Data owners and data risk managers are primary enforcers of standard data governance and management practices. Reviewing data classification and tagging are the key part of their job roles. Every domain/department should have a data officer to ensure data governance and provide reports to a data risk manager.
  •  Learning & Development – The cultural shift is required in terms of understanding the value of “Data” and implications of Data Risk. Mandatory training should be introduced around Data Risk and compliance requirements like GDPR. Standardize data handling practices should be promoted across the organization

Conclusion

In the current pandemic situation, where there is a significant increase in the culture of working from home or remotely and a continuous increase in cyber-attacks. Organizations need to start accessing their data management framework and the Data Risk associated with it. Review the current capabilities to mitigate that risk and develop a strategic roadmap in line with the Operational roadmap to implement any advancement to mitigate Data Risk.

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