I am a Data Analyst at Head Infotech Pvt. Ltd., a gaming company in Hyderabad. I have done my B. Tech from NIT Surat in Electronics & Communication Engineering. It was clear in my final year of graduation that I was not going to continue my career as an Electronics Engineer due to many reasons. This is the point where I thought of a career transition. Then, I researched about the areas where I can do well and for many obvious reasons, I was good at Mathematics, Statistics and Physics right from my childhood. This helped me in taking the decision to shift towards data science. It was a field where you can play with mathematics and logic to help answer difficult business problems using analytics.
I got to know about UpGrad’s PGDP in Data Science, with a certification from IIIT Bangalore, through one of my friends. After checking the course content, I found the pedagogy of content to be well organized. The reviews were very good as it was taught by professors from IIIT Bangalore. Even after that, I had a lot of discussions with many people along with the UpGrad mentor before arriving at the decision to take the course, as it was priced a little high for me. Finally, I enrolled in the course and it was the best decision I took just after completing my B. Tech. At some point in your life, you have to take a calculated risk to achieve success in life and this was it.
I had taken this online course leaving all the Electronics engineering knowledge and completely concentrating on Data Science. The content taught by IIIT-B professors made me more excited about this field. The support of UpGrad student mentors in the course was a crucial part. I followed them and they helped a lot in clarifying my queries. There was also placement assistance given where you are perfectly guided on how to start a career as a Data Analyst.
Checkout: Data Analyst Salary in India
When everything was going fine while learning all these, I got a call from Head Infotech Pvt. Ltd. to attend for an interview for Data Analyst role. After several rounds, finally, all my efforts after the graduation from my home, paid off – achieving career start as a Data Analyst. I would like to thank once again the IIIT-B professors and UpGrad for providing strong content and delivering such a huge course so systematically, and also Head Infotech Pvt. Ltd. for believing in me to join their family.
#data science #data #data analytics
If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.
If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.
In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.
#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition
For this week’s data science career interview, we got in touch with Dr Suman Sanyal, Associate Professor of Computer Science and Engineering at NIIT University. In this interview, Dr Sanyal shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.
With industry-linkage, technology and research-driven seamless education, NIIT University has been recognised for addressing the growing demand for data science experts worldwide with its industry-ready courses. The university has recently introduced B.Tech in Data Science course, which aims to deploy data sets models to solve real-world problems. The programme provides industry-academic synergy for the students to establish careers in data science, artificial intelligence and machine learning.
“Students with skills that are aligned to new-age technology will be of huge value. The industry today wants young, ambitious students who have the know-how on how to get things done,” Sanyal said.
#careers # #data science aspirant #data science career #data science career intervie #data science education #data science education marke #data science jobs #niit university data science
Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
In this article, we list down 50 latest job openings in data science that opened just last week.
(The jobs are sorted according to the years of experience r
Skills Required: Real-time anomaly detection solutions, NLP, text analytics, log analysis, cloud migration, AI planning, etc.
Skills Required: Data mining experience in Python, R, H2O and/or SAS, cross-functional, highly complex data science projects, SQL or SQL-like tools, among others.
Skills Required: Data modelling, database architecture, database design, database programming such as SQL, Python, etc., forecasting algorithms, cloud platforms, designing and developing ETL and ELT processes, etc.
Skills Required: SQL and querying relational databases, statistical programming language (SAS, R, Python), data visualisation tool (Tableau, Qlikview), project management, etc.
**Location: **Bibinagar, Telangana
Skills Required: Data science frameworks Jupyter notebook, AWS Sagemaker, querying databases and using statistical computer languages: R, Python, SLQ, statistical and data mining techniques, distributed data/computing tools such as Map/Reduce, Flume, Drill, Hadoop, Hive, Spark, Gurobi, MySQL, among others.
#careers #data science #data science career #data science jobs #data science news #data scientist #data scientists #data scientists india
Despite the impactful recession, job profiles like Data Scientist and Analyst have witnessed an exponential growth in various organisations. According to a recent study, amid the lockdown, specific domains and technologies across the IT space continue to develop at a steady pace. This has called for jobs like data analytics, AI, machine learning, deep learning, among others.
In this article, we list the six latest Data Science and Analysts jobs openings one can apply now.
#data analysts india #data analysts jobs #data science careers #data science jobs #data scientists india
The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.
This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.
As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).
This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.
#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management