From “nerve-racking ordeal” to “seamless data wrangling”.
Do you spend most of the time wrangling data and making it Analytics-Ready?
Tune in to D Cube Analytics Datalogue and discover Innovation triggers disrupting and digitizing the Life Sciences Commercialization model, Democratizing data analytics, Data Management, and embracing Data Science and AI.
D Cube Analytics Datalogue - Digital transformation with data transformation being the foundational pillar
A chat with industry veterans on innovations disrupting the Life Sciences space.
Host - Paramita Kar, Guest - Vishnu Maddileti and Rajeev Rangachari
Changing mindsets in digital non-native industry.
With real-world data upsurging and reshaping the pharmaceutical industry more than ever before, digital transformation has become a priority for pharma organizations.
As the patients and physicians are more digital-savvy these days, they expect the same benchmarks in their interactions with pharma organizations.
In the space of decision science and innovation, how do Life Science Organizations address challenges towards data availability and data silos?
Tune in to D Cube Analytics Datalogue and discover Innovation triggers disrupting and digitizing the Life Sciences Commercialization model.
11 Aug 2021
D Cube Analytics Datalogue - Everything around setting up data analytics processes including the kind of human resources needs and about enabling compliance at scale.
A chat with industry veterans on innovations disrupting the Life Sciences space.
Host - Paramita Kar, Guest - Vishnu Maddileti and Rajeev Rangachari
To innovate successfully, there is a strong need to have frictionless governance processes embedded to ensure compliance and security standards are met while no additional bottlenecks are created.
How do you provide a frictionless interface to several data citizens to utilize the Insight footprint to its potential?
Tune in to D Cube Analytics Datalogue and discover Innovation triggers disrupting and digitizing the Life Sciences Commercialization model, Democratizing data analytics, Data Management, and embracing Data Science & AI
11 Aug 2021
D Cube Analytics Datalogue - Business Applications and how new technologies like graph databases, etc. can be leveraged to productize outcome-oriented use cases
A chat with industry veterans on innovations disrupting the Life Sciences space.
Host - Paramita Kar, Guest - Vishnu Maddileti and Rajeev Rangachari
How do you convert insights to actionable strategies?
Tune in to D Cube Analytics Datalogue and discover Innovation triggers disrupting and digitizing the Life Sciences Commercialization model, Democratizing data analytics, Data Management, and embracing Data Science & AI
11 Aug 2021
D Cube Analytics Datalogue - Efficiently working on top of a good foundation with a focus on insight generation
A chat with industry veterans on innovations disrupting the Life Sciences space.
Host - Paramita Kar, Guest - Vishnu Maddileti and Rajeev Rangachari
The need for data democratization has become imperative in recent times. With self-serve tools and AI/ML, we can gain a competitive advantage in this data-driven world.
How can we make the process of data utilization productive, efficient, and Analytics-ready?
Tune in to D Cube Analytics Datalogue and discover Innovation triggers disrupting and digitizing the Life Sciences Commercialization model, Democratizing data analytics, Data Management, and embracing Data Science & AI
24 Jun 2021
An Analyst's Perspective; with Swetank Gupta
How an Analyst found Data Nirvana, from “nerve-racking ordeal” to “seamless data wrangling”.
Do you spend most of the time wrangling data and making it Analytics-Ready?
Is there a smarter and simpler way to explore data?
Know the daily challenges encountered by analysts on their journey to getting in-depth and meaningful insights while oscillating amongst numerous tasks.
Every business buzz around data to tap into its endless potential and drive actionable insights. Analysing these data provides the organization with an ability to make incremental decisions to drive success.
But, preparing the data for analysis is a daunting task considering the volume and complexities involved with it.
Therefore, the need for an intuitive and robust exploratory and transformation tool is more than ever before to fulfil the analysts’ requirements.
So, how can analysts address these issues to derive faster insights?
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