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Executive Summary
Nowadays, the importance of data analytics can hardly be underestimated in the corporate world. From a voluntary (and not necessary) application of basic statistics in 1990’s, data analytics has evolved to include descriptive, diagnostic, predictive and prescriptive analytics with powerful weapons such as SQL, Data Warehousing, Business Intelligence, Machine Learning, Big Data Analytics, IoT analytics, Deep Learning, and Data Visualization. This evolution, although indispensable, has brought with it a complicated dilemma. The “game” of data analytics is actually played between the business team, the analytics team and the IT team/department. The rules of this game have remained largely de-standardized in the last two to three decades. Consequently, a large number of analytics projects have failed in major industries with other problems such as improper resource utilization, monetary losses and un-optimized management practices.
More recently, the field of “data governance” has evolved to standardize the data analytics process in corporate sector. This 1-day workshop is all about data governance. It is particularly targeted towards Pakistan’s corporate sector, for implementing a data governance initiative and ensuring the success of any type of data analytics activity. The core elements of the workshop will focus on the rules for forming and managing a data governance council, methods for implementing the governance at the grass root level in the industry, and selecting the appropriate tools for coordinating governance activities. The workshop will terminate with a generic roadmap for implementing governance and useful corresponding tips to ensure success of data analytics.
A crucial point to mention is that data governance is a sub-category of the general domain of IT governance, which focuses on streamlining all IT-related activities in the organization. Considering the importance of IT departments in Pakistan’s corporate sector, this workshop will hence also discuss this streamlining process, and its relationship with data governance.
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Target Audience
The following audience are eligible to attend this workshop:
- Corporate business executives who are managing data analytics initiatives or departments in their industries, or who plan to launch such initiatives in the near future
- IT Managers and corresponding C-Level executives (CIO, CTO etc.)
- C-level executives/Business managers who are not necessarily related to the domain of data analytics
- Data scientists, Business Analysts, and BI Analysts
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Major Take-Aways
- A strategy to ensure successful execution of any type of data analytics activity
- A strategy to streamline all dimensions of business processes under the umbrella of IT departments
- How to apply data governance to ERP’s data execution paths (SAP and Microsoft Dynamics)
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Duration, Date & Time
1-day (9 am till 5 pm)
10th October 2020
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Fee
PKR 7,500 (Inclusive of all taxes)
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Trainer's Profile
Dr. Tariq Mahmood
Dr. Tariq Mahmood is an Associate Professor in the Faculty of Computer Science at IBA (Karachi). He is head of Big Data Analytics laboratory (BDA-LAB) at IBA, with focus on discovering optimized infrastructures for Big Data applications, and porting data science algorithms to Big Data platforms. Previously, he has served as the Chief Data Scientist with NexDegree and Vectracom. Dr. Tariq has successfully completed projects related to Big Data, Big Data Analytics, Big Data Infrastructure Development, Machine Learning, Autonomous Machine Learning, Business Intelligence, Data Warehousing, Customer Relationship Management, Data Governance and Encrypted Data Processing in the following industrial sectors: Stock Exchange, Telecommunications, Healthcare, Insurance, Retail/FMCGs, Oil & Gas and Governmental Organizations. Dr. Tariq has 10 years of professional and research experience in the aforementioned domains. He is a regular speaker, participant and panelist at local events targeting Data Science, Predictive Analytics and Big Data. He has conducted numerous training and workshops on Big Data and Data Science, both for Government and Private Organizations.