Lady Gaga's career began in 2005 when she was signed to Def Jam records but was later dropped. She began performing in clubs and experimenting with fashion. She then worked as a songwriter for Interscope and was signed by Akon, releasing her successful debut album The Fame in 2008. Her outfits and tour concepts are created by her creative team called Haus of Gaga. Initially her work was funded through the success of The Fame, and later through collaborations and successful tours. Lady Gaga's fans, called Little Monsters, see her as a role model for being unique and encouraging individuality and self-expression.
Whether you are music enthusiast or not, the best way you can express your feelings, anger, love, passion, joy and other kinds of feelings is simply through music. It is rightly said that when words and letters failed the best option is music. You will be able to express the intent of your heart through music which ordinarily may not be possible for you to either do in words or letters.
Whether you are music enthusiast or not, the best way you can express your feelings, anger, love, passion, joy and other kinds of feelings is simply through music. It is rightly said that when words and letters failed the best option is music. You will be able to express the intent of your heart through music which ordinarily may not be possible for you to either do in words or letters.
Having experience as Planning Engineer in the department of Project Management in Handling & Managing Projects works, along with Project Planning, Scheduling, Tracking and Reporting by using Primavera P6 & MSP (S-Curve, Catch up Plan,Delay Analysis)
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
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.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
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.
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.
2. When and how did Lady Gaga’s career begin?
• She attended New York University’s Tisch School for the arts but left to find
creative expression.
• Her career began when she was signed to Def Jam records in 2005. However, she
was soon dropped after. Because of this, she began to perform in clubs where she
started to experiment with more interesting fashion in New York.
• She then started to work as a song writer for Interscope Records where she wrote
for artists like Britney Spears and Pussycat Dolls etc.
• She was then signed up to R&B artist, Akon’s label called Konlive. He signed her up
after he saw her in a Burlesque show that she created called the “Lady Gaga and
the Starlight Revue.”
• After this, Gaga spent 2007 writing and recording The Fame which became a huge
success and in 2008/2009, her single Just Dance topped the charts as well as
Poker Face which topped the charts in almost all countries.
• Gaga took inspiration from the Queen song “Radio Ga-Ga” for her title and this is
how her career began.
3. Who creates her outfits and tour concepts?
• Although Gaga has an idea as to what she wants, her outfits and tour concepts are
decided and managed by her creative team called the Haus of Gaga. They make
her props and costumes for music videos and tours like The Monster Ball Tour and
one of most memorable outfits they made was her meat dress for the VMAs.
How is this funded?
• Her outfits and tour concepts were all funded through the money
she had received from The Fame – her album which became a
huge success and went global as soon as it was released. As well
as this, she was also an opening act for the Pussycat Dolls which
led on to more fame and wealth which she used for her tours and
outfits.
• Later on in her career, she also began to collaborate with other
famous artists like Beyoncé which again, made her become
wealthier, more famous and stronger within the business.
• Alongside this, her first tour The Fame, was such a huge success
that it allowed Gaga to go on a second world wide concert which
was called The Monster Ball Tour. When she finished The Fame
Ball tour in May 2011, her tour became the highest-grossing for a
debut headlining artist.
4. Research and describe Lady Gaga’s fans
• Lady Gaga’s fans are referred to as Little Monsters.
• Like Gaga, her fans are unique and quirky – no two are the same. They are
confident and they express themselves.
• Her fans are individual and don’t follow the crowd.
• She has quite a large LGBT fan base.
• They like to promote equality and tolerance as well as individualism; they like to
promote individuality – she tends to show this through her songs like Born this
Way.
• Her fans like to follow Gaga’s individuality; she allows them to feel confident in
themselves.
• They see Lady Gaga as a good role model because she doesn’t care about how
people see her.
5. Find 3 shocking or impressive outfits or accessories Gaga
has sported
6. What sorts of views does Gaga have about the world?
How do fans respond to this? Famous Quotes?
• Lady Gaga’s fans love the fact that Lady Gaga is unlike any other artist. She is unique and isn’t afraid to be
herself. It makes her fans feel confident about having views about the world because Gaga wants her
fans to be brave and stand up for what they believe in; she doesn’t want them following the crowd. She
encourages her fans to be different and to speak up thus why her fans adore her.
“What I've learned is that you really
don't need to be a celebrity or have
money or have the paparazzi following
you around to be famous.”
“Some women choose to follow men, and some women
choose to follow their dreams. If you're wondering which way
to go, remember that your career will never wake up and tell
you that it doesn't love you anymore.”
“Trust is like a mirror, you can fix it if it's broken, but you can
still see the crack in that mother fucker's reflection.”
“Don't you ever let a soul in the
world tell you that you can't be
exactly who you are.”
“You have to be unique, and different,
and shine in your own way.”
“And now, I'm just trying
to change the world, one
sequin at a time.”
“Sometimes in life you don't always feel like a winner, but that
doesn't mean you're not a winner, you want to be like yourself.
I want my fans to know it's okay.”
• Gaga simply believes in equality.
She stresses how we should love
all and do all that we can to help
those around us; we should
make our life worth living and try
and make an impact/difference
on the world.