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Big Data Analytics

VP and Head Data Monetization Sricharan Vadapalli talks about Big Data Analytics course, what is Big Data Analytics and other details about a Career in Big Data Analytics.

















Big Data Analytics

Sricharan Vadapalli | VP and Head Data Monetization | Suneratech






What is Big Data Analytics?


You may be curious about a Career in Big Data Analytics. Unfortunately, it is very difficult to find information about What Big Data Analytics actually is. Most pages on the internet just talk about How to get into Big Data Analytics. Just like you would normally not trust a non Doctor with names of medicines, you should also not trust opinions about Big Data Analytics from non professionals.

VP and Head Data Monetization Sricharan Vadapalli invested 7 years & 7 months in Big Data Analytics. VP and Head Data Monetization Sricharan Vadapalli outlines Big Data Analytics as:

Big Data analytics is the often complex process of examining large and varied data sets from multiple sources called big data to uncover valuable business information including hidden patterns, unknown correlations, market trends and customer preferences that can help organisations derive informed business intelligence and decisions.





How VP and Head Data Monetization Sricharan Vadapalli got into Big Data Analytics?


I joined IT MNC from college and worked for a Product Company for 8 years mostly in USA. I have also worked with MNC's and Startups. . I am currently working with Sunera Tech as VP and Practice Head of Data Monetization ( Analytics, Machine Learning, Devops on Cloud). My books are on DevOps, Big Data and successful Relationships. Learning was my passion, I am certified SAP Hana consultant also certified in PMP, ITIL, OCA, INS21, FP, In Memory, I was always passionate about data and its value at the enterprise level hence I found my way into Big data Analytics. I have authored books on DevOps, Bigdata and relationships.





VP and Head Data Monetization Sricharan Vadapalli's Talk on Big Data Analytics


Session Image
The Journey of a Data Analyst: Sreecharan Vadapali’s Insights into Big Data Analytics


In the rapidly evolving field of technology, few areas are as pivotal as Big Data Analytics. Sreecharan Vadapali, a seasoned technology professional with nearly two decades of experience, embodies this dynamic sector. With an impressive educational background and a career that spans several leading firms, including Tata Consultancy Services and Infosys, Sreecharan has carved a significant niche in data analytics. This article delves into Sreecharan's personal journey, the educational requirements, essential skills, advantages, challenges, and a typical day in the life of a data analyst, offering readers a comprehensive understanding of this exciting and vital career.

What Is Big Data Analytics?

Big Data Analytics refers to the process of examining large and complex datasets to uncover hidden patterns, correlations, market trends, and customer preferences. As Sreecharan explains, analytics is not just about handling data but understanding its lifecycle—how it is collected, processed, and ultimately transformed into actionable insights. This career allows professionals to navigate through various stages of data management, shaping organizational strategies that drive business success. With the proliferation of data in today’s digital landscape, analytics has become crucial for businesses aiming to leverage data-driven decision-making.

Education

Data Lifecycle Management

### Data Lifecycle Management Image

Sreecharan emphasizes the importance of understanding data lifecycle management, which involves the stages of data from its creation to its eventual disposal. Learning about how data is integrated, processed, and reported is foundational for anyone aspiring to work in data analytics. His exposure to various facets of this lifecycle, particularly during his tenure at Tata Consultancy Services, has enabled him to appreciate how crucial proper data management is for producing reliable information and insights.

Data Integration

### Data Integration Image

A core aspect of data lifecycle management highlighted by Sreecharan is data integration, the process of combining data from different sources. This requires a careful approach to ensure that all relevant data is accurately gathered and synthesized. Sreecharan draws parallels with a school setting, where data from various subjects is compiled to create a comprehensive attendance report. Understanding this principle is vital as it forms the bedrock for effective data analysis in larger organizations.

Data Modelling

### Data Modelling Image

Data modeling is another crucial area that Sreecharan identifies as key to effective analytics. It involves organizing data in a format that facilitates processing and analysis. This skill is particularly sought after, as mismodeled data can lead to incorrect reporting and, consequently, poor business decisions. Sreecharan's experience highlights that creating robust data models within multinational settings adds complexity but is essential for generating meaningful insights.

Reports & Dashboards

### Reports & Dashboards Image

Generating reports and dashboards is the culmination of data analysis, delivering insights that inform decision-makers. Sreecharan notes that the ability to create insightful reports is paramount, with tools ranging from basic spreadsheet applications to advanced visualization software like Tableau. Mastering the art of reporting ensures that organizations can interpret their data efficiently and correctly, and the choice of tools can significantly influence the effectiveness of this process.

Software & Tools

### Software & Tools Image

Familiarity with various software and tools is essential for anyone in the field of data analytics. Sreecharan underlines the continuous evolution of tools used in data integration, modeling, and reporting. Knowledge of platforms like Informatica for data integration or specialized tools for different sectors such as insurance or retail is invaluable. This technical knowledge, combined with a willingness to adapt, is crucial for success in the ever-changing landscape of big data.

Skills

Analytical Skills

### Analytical Skills Image

Sreecharan emphasizes that strong analytical skills are foundational to effective data analytics. The ability to interpret complex datasets accurately and derive insightful conclusions is essential. As he explains, analytical skills extend beyond technical abilities to include common sense and awareness of the data's implications, ensuring accurate and meaningful reporting.

Statistical Skills

### Statistical Skills Image

Mathematical knowledge and statistical skills are another key component of Sreecharan's toolkit. Understanding statistical methods enables data analysts to interpret results effectively. As the demand for more sophisticated analytics continues to grow, those with a strong foundation in statistics are likely to find themselves in high demand, leading to lucrative career opportunities.

Domain Expertise

### Domain Expertise Image

Domain expertise plays a significant role in data analytics, as understanding specific industry needs is crucial for formulating effective models and reports. Sreecharan points out that whether working in banking or insurance, familiarity with the sector's unique challenges and requirements is essential to producing tailored insights that can drive business outcomes.

Marketing Skills

### Marketing Skills Image

Although not traditionally highlighted in data analytics, Sreecharan believes that marketing knowledge can significantly enhance an analyst's ability to connect with stakeholders. Understanding market dynamics helps in creating data stories that resonate with decision-makers, thus bridging the gap between data-driven insights and practical business applications.

Programming Skills

### Programming Skills Image

Lastly, programming skills are increasingly becoming necessary in the toolbox of data analytics professionals. Sreecharan notes that while many tasks can be accomplished using existing tools, customizing these solutions often requires coding knowledge. This capability allows professionals to adapt data systems to better meet organizational needs and stay relevant in a fast-paced work environment.

Positives

Always in Demand

### Always in Demand Image

One of the most compelling aspects of a career in big data analytics is its consistent demand. Sreecharan points out that as organizations increasingly rely on data-driven strategies, the skills of analytics professionals are continually sought after. This demand is reflected not only in job opportunities but also in the investment that companies are making in data-centric solutions.

Monetary Potential

### Monetary Potential Image

Sreecharan notes the monetary benefits associated with a career in data analytics. With the industry evolving rapidly, skilled professionals can command competitive salaries that often far exceed those in other fields. This financial incentive, particularly for data scientists and analysts with specialized skills, plays a vital role in attracting talent to this area.

Always Learning

### Always Learning Image

The nature of data analytics ensures that professionals are always learning. As new data sources emerge and technologies evolve, staying informed about the latest trends is crucial. Sreecharan highlights that this continuous learning aspect keeps the field exciting and dynamic, catalyzing innovation and adaptability among practitioners.

Better Money Investments

### Better Money Investments Image

Companies are increasingly recognizing the importance of investing in data analytics capabilities. Sreecharan observes that successful organizations often devote resources to developing robust analytics teams, which opens doors for professionals to thrive in environments that value data as an asset. This investment translates into better career opportunities and more substantial professional growth.

Challenges

Knowing Every Aspect

### Knowing Every Aspect Image

Despite the benefits, Sreecharan acknowledges that one of the main challenges in big data analytics is the breadth of knowledge required. Professionals often find themselves specializing in certain areas, such as data integration or modeling, which can limit their exposure to the entire data lifecycle. Overcoming this challenge requires a commitment to continuous learning and cross-functional collaboration.

Data Volume

### Data Volume Image

The sheer volume of data presents another challenge. Sreecharan notes that understanding how to manage and analyze large datasets effectively can be daunting. Analysts must be equipped with strategies to handle the complexities of big data environments while ensuring data integrity and accuracy.

Knowledge Up-dation

### Knowledge Up-dation Image

Keeping skills up to date is crucial in the fast-evolving field of data analytics. Sreecharan emphasizes the need for ongoing education and adaptation to new tools, methodologies, and market dynamics. Failure to stay current can diminish a professional’s relevance and effectiveness in their role.

Outdated Systems

### Outdated Systems Image

Many organizations still operate on legacy systems that pose significant barriers to modern data management practices. Sreecharan highlights the wariness that companies have in moving away from these established systems, posing challenges for analytics professionals who seek to implement innovative solutions. Convincing stakeholders of the benefits of modernization is both a challenge and an essential task.

A Day Of

Product Management

### Product Management Image

A typical day as a data analyst involves engaging with various stakeholder requests, particularly around product management and development challenges. Sreecharan describes a day filled with addressing issues related to data integration, modeling requirements, and reporting accuracy. Collaboration is key, as analysts work alongside business teams to refine models and generate insightful reports that drive strategic decisions. This multi-faceted role showcases the dynamic nature of data analytics, with each day presenting new challenges and opportunities for learning and growth.

The journey of a data analyst is both challenging and rewarding, marked by continuous learning and adaptation. As industries increasingly rely on data to drive their decisions, professionals like Sreecharan Vadapali play a vital role in shaping the future of business intelligence and analytics. This career not only offers significant financial rewards but also the satisfaction of being at the forefront of technological advancements that drive change across various sectors.





Install the LifePage App to:


  1. (for Free) Watch VP and Head Data Monetization Sricharan Vadapalli’s full Big Data Analytics Career Talk

  2. ₹ Do a Self Assessment on Big Data Analytics to calculate your Dream Index, which is defined as:

    According to Sricharan Vadapalli your chances of success in Big Data Analytics is __%

  3. Access your personalized Dream Index Report which will have all your Dream Indices sorted in descending order.

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How to get into

Big Data Analytics?



If you are want to get into Big Data Analytics, start by investing in a Career Plan.

The 14 hour process, guided by a LifePage Career Advisor, will help you introspect and check whether your interest in Big Data Analytics is merely an infatuation or is it truly something you wish to do for the rest of your life.

Next, your Career Advisor will help you document how you can get into Big Data Analytics, what education and skills you need to succeed in Big Data Analytics, and what positives and challenges you will face in Big Data Analytics.

Finally, you will get a Career Plan stating which Courses, Certifications, Trainings and other Items you need to do in the next 7 years to become world’s best in Big Data Analytics.





LifePage Career Plan

14 hour personalized guidance program















Your LifePage Career Advisor facilitates your guided introspection so that you systematically explore various Career options to arrive at a well thought out Career choice.

Next: your Advisor helps you figure out how you will get into your chosen Career and how will you develop the skills needed for success in your Chosen Career.

LifePage Plan will not stop at saying "to become an Architect study Architecture". It will guide you on which Certifications, Trainings and Other items you need to do along with your Architecture education to become the world's best Architect.











Links for this Talk




VP and Head Data Monetization Sricharan Vadapalli's LifePage:


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[LifePage]
https://www.lifepage.in/page/sricharanvadapalli






LifePage Career Talk on Big Data Analytics


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[Career]
https://www.lifepage.in/careers/big-data-analytics


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[Full Talk]
https://lifepage.app.link/20190221-0002


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[Trailer]
https://www.youtube.com/watch?v=eku7tVbt7t0


(Big Data Analytics, Sricharan Vadapali, Pyramid Solutions, Practice Head, Data Analytics, Data Interpretation, Data Analysis, Modeling Data)







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