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This ebook is all about data analysis, what are the steps involved in data analysis and what are the techniques. We will bring out a detailed course very soon. pls register https://excelfinanceacademy.zenler.com/ to save over 80% cost
Data Analysis Methods 101 - Turning Raw Data Into Actionable InsightsDataSpace Academy
Data analytics is powerful for organisations. It can help companies improve their overall efficiency and effectiveness. The blog offers a step-by-step narration of the data analysis methods that will help you to comprehend the fundamentals of an analytics project.
Data analysis is identifying trends, patterns, and correlations in vast amounts of raw data to make data-informed decisions. These procedures employ well-known statistical analysis approaches, such as clustering and regression, and apply them to larger datasets with the assistance of modern tools.
The Annual G20 Scorecard – Research Performance 2019 bhavesh lande
The 2019 G20 Summit takes place in Osaka, Japan
on June 28-29. What happens in the G20 affects
the world and the G20 group is undoubtedly
a driver in the global research system.
information control and Security systembhavesh lande
Get an overview of threats to the Organization
• Learn about technologies for handling Security
• Get an overview of wireless technology
• Understand managing security
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Data Analysis Methods 101 - Turning Raw Data Into Actionable InsightsDataSpace Academy
Data analytics is powerful for organisations. It can help companies improve their overall efficiency and effectiveness. The blog offers a step-by-step narration of the data analysis methods that will help you to comprehend the fundamentals of an analytics project.
Data analysis is identifying trends, patterns, and correlations in vast amounts of raw data to make data-informed decisions. These procedures employ well-known statistical analysis approaches, such as clustering and regression, and apply them to larger datasets with the assistance of modern tools.
The Annual G20 Scorecard – Research Performance 2019 bhavesh lande
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on June 28-29. What happens in the G20 affects
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a driver in the global research system.
information control and Security systembhavesh lande
Get an overview of threats to the Organization
• Learn about technologies for handling Security
• Get an overview of wireless technology
• Understand managing security
information technology and infrastructures choicesbhavesh lande
Understand information technology infrastructures
• Get an overview on infrastructure decision
• Learn about infrastructure components
• Understand infrastructure solutions
• Know what are the main drivers of innovation in IT
• Understand how innovations spread
• •Understand impact of firms innovating with IT
• •Get an overview of some recent innovations driven by IT
1.Industry transformation
2.Diversity and variety
3.Personalisation
4.Experimentation
5.Plug-and-play innovations
6.New marketing opportunities
7.Use of smart technologies
8.Natural language interfaces
9.Analytics
10.Crowd sourcing
database application using SQL DML statements: Insert, Select, Update, Delet...bhavesh lande
Design at least 10 SQL queries for suitable database
application using SQL DML statements:
Insert, Select, Update, Delete with operators, functions, and set operator.
WHY
WHERE
HOW
WHEN
WHO
FOR WHAT
Defining Data Science
• What Does a Data Science Professional Do?
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Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
1. Statistics Techniques To Deal With Data
Data Collection
The first activity that needs to be performed before undertaking any statistical analysis project is
collecting relevant data/information. Data is mainly gathered from two sources- primary and
secondary. Primary sources refer to the data collected by the researcher himself and secondary
data is collected from outside. Primary data is original while the secondary data is hardly original
at times. Primary data includes surveys, observations, and experiments. Secondary data has
internal records and government published data.
Data Categorization And Classification
Categorization needs the data to be organized in order to get some insights from it. Basic
insights about the data can be obtained through the various listing of values in an ordered array.
For example, we have data of heights of 10 people
160cm, 165cm, 155cm, 190cm, 177cm, 181cm, 179cm, 185cm, 159cm, 173cm
This data in an ordered array will look like
155cm, 159cm, 160cm ,165cm, 173cm, 177cm, 179cm, 181cm, 185cm, 190cm
The above data tells us that 155cm is the shortest height while 190cm is the tallest.
Data classification is the assembly of relevant facts/data into different categories/groups as per
certain features. It helps in compressing portions of data in order to differentiate between the
similarities and dissimilarities in the data. It encourages association. The factors, based on
which classification is done are
• Geographical
• Chronological
• Qualitative
• Quantitative
• Geographical classification
It is classified on the basis of geographical location. For example, classifying colleges
based on which state they belong to.
• Chronological classification
It is divided on the basis of time. For example, babies born in a hospital in the current
year and last year.
• Qualitative classification
It is ranked on the basis of some attributes. For example, classifying people based on
area, gender, and literacy.
• Quantitative classification
2. It is organized as per quantitative class intervals. For example, classifying individuals
based on their annual income.
Data Presentation
Presentation of data includes frequency distribution which has a group of data split into mutually
exclusive categories conferring the frequency of observations in each class.
Constructing a frequency distribution involves
• Determining the question to be addressed
• Collecting raw data
• Organizing data (frequency distribution)
• Presenting data (Histogram)
For example, assume you are looking for prospective clients for your new product which is an
electric bike. You want to target a particular section of IT employees in some locations of your
area. From your past experience, you know that people who travel up to 10 km every day to
their offices are more interested to buy this product. As reaching each and every employee in
the IT park may incur a huge cost, you decided to do a pilot survey to get some idea about the
prospective market of your product in the IT park. You engaged an executive who was
supposed to ask every employee coming to the office in the morning about how much time they
need to reach the office. This data can then be used to calculate the number of potential
customers who are interested in your product.
