Data Analytics with Managerial Applications InternshipJahanvi Khedwal
Data Analytics with Managerial Applications Internship under Prof. Sameer Mathur-Making Advanced Analytics Work for You by Dominic Barton and David Court-presentation
Take a look at this interesting presentation on ➡ 3 Pillars to become successful with your analytics strategy
Inculcate a culture of analytics, have the right people on-board, get your organization strategy on one page, and have the right architecture and data management strategies in place.
Link: https://bit.ly/2BanJcW
Data Analytics with Managerial Applications InternshipJahanvi Khedwal
Data Analytics with Managerial Applications Internship under Prof. Sameer Mathur-Making Advanced Analytics Work for You by Dominic Barton and David Court-presentation
Take a look at this interesting presentation on ➡ 3 Pillars to become successful with your analytics strategy
Inculcate a culture of analytics, have the right people on-board, get your organization strategy on one page, and have the right architecture and data management strategies in place.
Link: https://bit.ly/2BanJcW
Making Advanced Analytics Work for You by Dominic Barton and David CourtKASHISH MUKHEJA
This is a presentation on the article Making Advanced Analytics Work for You by Dominic Barton and David Court.I have made the presentation as a task on my data analytics internship by Prof. Sameer Mathur.
These are my insights on the article "Making Advanced Analytics Work for You" by Dominic Barton and David Court. This is an assignment, part of data analytics internship
Making advanced analytics work for you.
Big data and analytics have rocketed to the top of the corporate agenda. Executives look with admiration at how Google, Amazon, and others have eclipsed competitors with powerful new business models that derive from an ability to exploit data....
How data scientists add value to your business organizationJanBask Training
Mostly data scientists are being trained in computer science, math and statistics. The expertise of data scientists can be used in data visualization, data mining, and the information management.
https://www.janbasktraining.com/data-science
This power point presentation tell us about the transform the way companies do business. What are the problem faced by the company. What is advanced analytics, and why its used.
In order to make decisions in business, analysts drive data from various sources. it will be put to test. later forecasts are made. Thus, business analysis is a process to analyze the business data so that decisions can be made
Making Advanced Analytics Work for You by Dominic Barton and David CourtKASHISH MUKHEJA
This is a presentation on the article Making Advanced Analytics Work for You by Dominic Barton and David Court.I have made the presentation as a task on my data analytics internship by Prof. Sameer Mathur.
These are my insights on the article "Making Advanced Analytics Work for You" by Dominic Barton and David Court. This is an assignment, part of data analytics internship
Making advanced analytics work for you.
Big data and analytics have rocketed to the top of the corporate agenda. Executives look with admiration at how Google, Amazon, and others have eclipsed competitors with powerful new business models that derive from an ability to exploit data....
How data scientists add value to your business organizationJanBask Training
Mostly data scientists are being trained in computer science, math and statistics. The expertise of data scientists can be used in data visualization, data mining, and the information management.
https://www.janbasktraining.com/data-science
This power point presentation tell us about the transform the way companies do business. What are the problem faced by the company. What is advanced analytics, and why its used.
In order to make decisions in business, analysts drive data from various sources. it will be put to test. later forecasts are made. Thus, business analysis is a process to analyze the business data so that decisions can be made
Table of ContentsIntroduction. 2Summary of the busines.docxjohniemcm5zt
Table of Contents
Introduction
.
2
Summary of the business
.
3
Benefits and disadvantages of Business Analytics
.
3
Challenges that the organization may face using business analytics.
5
Business Analytic Techniques That the organization Can Use
.
6
The Implementation Plan
.
7
Backup plan
.
8
Conclusion
.
8
References
.
9
Introduction
Analytics refers to discovering, interpreting and communicating important patterns in collected data. Analytics has been used in organizations since exercises in managements were put into place by Frederick Winslow Taylor in the late 19th century.
Today, with the introduction of computers in day to day running of businesses, organizations and most of the institutions, the use of analytics has been brought to a whole new level. These consequential patterns can help in decision making in different scenarios.
Business analytics refers to the proficient use of technologies in continuously exploring and investigating past business performance so as to make inferences and help in business planning and decisions. Predictive modeling and statistical methods are extensively utilized to help the management in making this decision.
Business analytics are applicable in a wide range of business and organization scenarios to help in making management decisions. Business analytics has been changed the way businesses look at their key indicators of performance.
The business analyst has responsibilities in the following areas:
They help in identifying the technical actions that would address a certain situations, also supports in delivering the business strategies.
They help in defining procedures they will use in organizations.
They help in supporting the implementations and operations of strategic plans.
They refine the techniques once they have implemented in order to tolerate changes while ensuring continued alignment with the business strategy.
Business Description
The firm is involved in the design. Design firms make designs to clients to meet their (clients) needs.
The business analytics can use different methods analytical techniques. For example, the orders for particular graphic designs vary seasonally due to upcoming promotions and holiday season. The firm should use business analytics to know when in the past they experience different designing orders. The firm should use business analytics to analyze data so that it can be able to make informed decisions.
The organization possesses technological equipment’s but they do have any integrated system. The business should use analytics to connect its databases for easy access and efficiency of information flow.
The firm should also use business analytics to predict how the business would perform in a new environment it wishes to venture into. It would analyse all the factors that would seemingly impact its operations and success in the new environment.
Benefits and disadvantages of Business Analytics
Benefits
Business analytics creates a better .
CPG Companies: Evolving Your Analytics-driven Organizationsaccenture
Accenture surveyed 90 large, global consumer packaged goods companies and found three important dimensions toward building an analytics-driven organization.
Read our other analytics research on accenture.com: http://www.accenture.com/CPGanalytics
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdf
Making Advanced Analytics Work for You by Dominic Barton and David Court
1. Making Advanced
Analytics
Work for You.
This presentation is made as a part of
Data Analytics internship by
Prof. Sameer Mathur
at IIM Lucknow.
2. Benefits of Advanced Analytics
For Business :
-Forecasting
-Enhancing Performance
-Decision making
-Developing New product
or services
For Government :
-Preventive Actions
-Rule making
-Decision making
3. Skepticism among Managers
-They’re convinced that their
organizations simply aren’t ready.
-Big Investments
-Misunderstanding of traditional data.
11. Build models that Predict,
Optimize business outcomes
-Need to Identify
the business
opportunity and
determine how the
model can improve
performance.