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Posts Tagged ‘data analytics’

How can governments leverage data to improve performance?

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Islam Salahuddin is a data analyst with a strong focus on storytelling and data visualization, growing statistical knowledge, and developing a set of technical skills and tools. As an expert in data analysis at The KPI Institute, Islam leads the generation of research on the domain of data analytics and the development of business analytics toolkits.

Future-forward: using data analytics in app development

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Jino Noel is a data science and technology leader with extensive experience in building data teams and practices across different organizations. His experience ranges from working in startups to large conglomerates across both Australia and the Philippines. At the time of this interview, he was the Chief Data Officer at Data Analytics Ventures, Inc. (DAVI). Currently, he is the Chief Data Officer at Angkas.

What are the key skills that a Chief Data Officer should possess nowadays?

A Chief Data Officer should have both data-related technical expertise as well as people leadership skills. Leading will always be part of the job, particularly for highly specialized technical people such as data engineers and data scientists. To be able to lead them properly, I believe it is better to be a technical person myself, so I can discuss technical matters fluently, which helps me gain their trust.

What data-related challenges have you faced as the Chief Data Officer of DAVI? How did you overcome these challenges?

Our data-related challenges are the same as any company. Being able to trust our data, cleaning up data from our sources, data latencies, and other related issues. DAVI overcame these by investing in people—hiring high-quality experts in our data engineering, data governance, and analytics teams to help us make sense of the data coming in—and building robust data pipelines that have increased the standard of quality of the data in our data lake.

How does DAVI make use of advancements in artificial intelligence (AI) and machine learning to help its clients understand their customers’ needs and buying patterns?

DAVI has recently started using machine learning to model our users’ propensity to buy certain products. This helps us create more accurate target audiences for our precision marketing campaigns. We are also moving forward with a recommendation engine project, with the goal of improving user engagement with our retail partners and with our promos and campaigns. On top of this, we are improving our machine learning operations expertise to make our model deployments repeatable and robust.

In the digital marketplace, data analytics acts as a guiding compass for app developers, enabling the creation of personalized, high-performing applications that align with user preferences. By leveraging data, developers can understand nuanced user behaviors and preferences, allowing them to tailor apps to meet specific user needs and aspirations.

Dive deeper into these discussions by reading Jino Noel’s full interview with The KPI Institute. Download the free digital copy of PERFORMANCE Magazine Issue No. 26, 2023 – Data Analytics on the TKI Marketplace. You can also purchase a  physical copy via Amazon

How to achieve business goals with data analytics

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Harry Patria, the CEO of Patria & Co., is a data strategist and lecturer who founded a company that serves over 100 corporate clients, 200 analytical platforms, and 500 professionals. He is a Data Hackathon winner in the UK and graduated with distinction from his master’s degree to a PhD program with a fully-funded scholarship. Harry is a subject matter expert in several fields.

Data buddies: bridging the gap between data analysts and non-technical team members

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Dietmar Böhmer joined Tyme seven years ago and he has been leading the data and analytics function across the group, which includes TymeBank in South Africa and the newly launched GoTyme in the Philippines. He has led lending, data science, machine learning, and big data teams in banking for close to two decades and has lectured in the actuarial field prior to that.


How Data Analytics Can Improve Company Performance

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Image Source: fauxels | Pexels

The business intelligence and analytics industry reached over $ 19 billion globally in 2020, albeit the derailed economic performance caused by the pandemic.  The business intelligence market growth experienced a 5.2% increase, and the data analytic growth rate is expected to rise in the coming years as companies realize the need to manage data to make better decisions.

According to Angela Ahrendts, a former retail Vice President at Apple Inc., customer data is the most significant differentiator among businesses in this era. Companies that know how to maneuver heaps of data to create strategic moves usually succeed. To determine how companies adopt and implement data analytics, let’s first understand how data can make a company’s operations efficient. 

Data Analytics: Four Ways to Increase Company Performance

As discussed earlier, data analytics is beneficial for making more accurate business decisions. Managers and executives can take action on the data insights they get to drive better competitive advantages in their markets. There are four ways data analytics can accelerate business performance:

The first way is by creating informed decisions. One of the key benefits that businesses look out for when dealing with data analytic solutions is developing better and more accurate decisions from the insights they get from analyzing data. 

There are two processes that ensure the development of better decisions: predictive analytics and prescriptive analytics. Prescriptive analytics are utilized to project the way companies react to forecasted trends, whereas predictive analytics focus on events that might occur after analyzing collected data.

Improving efficiency is another route. Data analytics is highly beneficial especially in the operation management for streamlining operations. For example, companies can retrieve and assess their data relating to supply chains to discover where delays in their supply networks happen or to forecast areas where problems emerge and use these insights to prevent any issues.

Data analytics also enables risk mitigation. To cut down losses, data can be utilized to reduce physical and financial risks in business. Through collecting and assessing data, inefficiencies can be either identified or predicted. Also, potential risks are revealed to inform management on creating preventive policies. 

Lastly, data analytics enhances security. As many businesses confront numerous data security threats in today’s era, it is essential to keep the company’s cybersecurity out of dangerous attacks that cause financial or brand image blow. A company can evaluate, process, and draw insights from its audit logs to showcase the source of previous cyber breaches. The outcome of this exercise would be to recommend possible remedies to the problem.

Join The KPI Institute’scertification course on data analysis today to learn more about data analytics, improve your analytical skills and make wise business decisions.

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