#Analytics Intelligence

[salesmarkglobal]

Strategies for Effective Business intelligence and Analytics Implementation

Today’s business world regulates and operates on data generation, which makes data crucial for businesses, as it helps them derive actionable insights. Business intelligence [BI] is a model that helps you transform huge amounts of data into valuable insights that guide you in making informed decisions for your business.

This blog post is meant to underscore the essence of BI in the area of data-based decision-making. We will discuss the practical aspects of BI platforms and how they form the backbone of business institutions’ growth.

Read the Complete Article- 5 Ways to Leverage Business Intelligence and Analytics for Your Business 

Drive strategy with insights. Explore Our Analytics Intelligence now!

#BI tools #Business Intelligence #customer satisfaction #market trends #BI platforms #business strategy #BI systems #marketing automation #CRM #Analytics Intelligence #marketing automation systems #Data mining #data mining strategies #account based marketing #abm #b2b marketing #business analytics #abm strategy #data analytics

[nitor-infotech]

Data Analytics: Techniques & Tools

#data analysis #business analytics #big data analytics #predictive analytics #analytics intelligence #business data analytics #reporting analytics #data analytics companies #data insights

[mindblowingscience]

New research has uncovered the potentially harmful substances that are produced when e-liquids in vaping devices are heated for inhalation. The study, published in Scientific Reports, highlights the urgent need for public health policies concerning flavored vapes. The research team at RCSI University of Medicine and Health Sciences, Dublin, used artificial intelligence (AI) to simulate the effects of heating e-liquid flavor chemicals found in nicotine vapes. They included all 180 known e-liquid flavor chemicals, predicting the new compounds formed when these substances are heated within a vaping device immediately prior to inhalation. The analysis revealed the formation of many hazardous chemicals including 127 which are classified as "Acute Toxic," 153 as "Health Hazards" and 225 as "Irritants." Notably, these included a group of chemicals called volatile carbonyls (VCs) which are known to pose health risks. Sources for VCs were predicted to be the most popular fruit, candy and dessert-flavored products.

Continue Reading.

#Science #Chemistry #Analytical Chemistry #AI #Artifical Intelligence #Machine Learning #Vapes #Nicotine Vapes #E-liquids

[fromtheseventhhell]

It's "the Stark sisters have complementary skillsets" until someone points out that Arya is good at math and Sansa isn't. Then suddenly Arya is an unreliable narrator, Sansa is just being humble, and she'll magically have that skill if/when it becomes relevant

#the absolute refusal of this fandom to believe that Arya is better at an /intellectual/ subject than Sansa is ridiculous #and the funniest part is that Sansa explicitly states she isn't good at math herself but people still pretend not to see it #they want to force the brain and brawn shit on them sooooo badly and it's just never gonna work because Arya is incredibly intelligent #and that's constantly reinforced...her being good at math just introduces how analytical she is which is a HUGE part of her character #the irony of the /don't pit the sisters against each other/ stans doing the most to compare and divide their stories + characters #if they didn't base their takes on fanon it wouldn't be an issue though 🤷🏾‍♀️ #so funny to bring up the fact that Arya is canonically good at math cause it goes against basically every fandom idea about her #that along with her overall intelligence cause they can't handle her being more then someone's bodyguard

[turns-out-its-adhd]

AI exists and there's nothing any of us can do to change that.

If you have concerns about how AI is being/will be used the solution is not to abstain - it's to get involved.

Learn about it, practice utilising AI tools, understand it. Ignorance will not protect you, and putting your fingers in your ears going 'lalalala AI doesn't exist I don't acknowledge it' won't stop it from affecting your life.

The more the general population fears and misunderstands this technology, the less equipped they will be to resist its influence.

#ai #artificial intelligence #ai technology #tech #technology #singularity #futurism #datascience #data analytics #data harvesting #manipulation #civil rights #civil disobedience #ai discourse

[stuckinapril]

Being a girl w a genuinely drop-dead gorgeous mom can be so psychically damaging bc why does my mom have honey-brown eyes and warm blonde hair and glowing porcelain skin and full lips and a naturally slender figure ??? And when I was a little girl I legit thought she was a model bc she’s so pretty????? She has instilled me w a lot of self-confidence about my looks so like it’s fine but still!!! It is hard not to compare yourself when ur mother is beautiful without even trying

#where’s that one quote that’s like the dichotomy of having a mother who’s also very pretty etc etc #oh AND brains. she’s an engineer & a total workaholic & so analytical & smart #she taught me women can be pretty and intelligent ever since I could walk <3 #i luv my mom sm it’s tru #p

[lotus-pear]

HIHI!!! first of all i love your art sm i love your design for chuuya and the soft lookin coloring stylee... oh i started to get off topic lmao ANYWAYS. what's your opinion on Nikolai ? i think he is very silly but also an interesting character. i'd love to see your take <3

first of all THANK YOU that’s so sweet🥺

secondly i find his character very complicated and interesting. he truly is doomed by the narrative yet intertwined with it in a tragic way. he reminds me of a fallen angel, someone who has had their wings broken yet still wishes to fly once more. the whole wanting to be free of all emotions and leave his mortal shell behind, ascending to free will and essentially divinity, is actually something ppl who read are able to sympathize with. seeing love and attachment as worldly desires and wanting to cast them aside, yet still being the character who sets an entire trial as a test of love. him being like “i’m perfectly sane”? he actually is. he’s conscious of what he’s doing and clear on his motives and will do anything to achieve them, going to any length, any extreme. that’s what makes him such a compelling villain.

#I LOVE NIKOLAI IF U COULDNT TELL?? #i never talk abt him but i will defend that mf w my life he is so so so pookie babygirl i love him sm #seeing him devestated in the finale actually took years off my life #he’s so fucking well written and lots of ppl don’t see that bc he puts on a facade of being silly and whimsical #but he’s actually a very emotionally intelligent and scarily analytical man #anyway live laugh love nikolai #lotus’s asks

[theicarusconstellation]

sometimes i’m convinced that people who didn’t see paul’s corrupt arc coming in dune messiah just didn’t read the time skip in dune at all

#it’s so obvious #and i love paul for it #go off you silly confused fool #you never wanted godhood but now that you have it perform a silly little dance #i can look at his character analytically #and intelligently #but i also know how to have fun #so he’s my babygirl outside of intellectual discussion #paul atreides #he wanted to be a legendary hero and ended up a legendary corruption #corrupted protagonists >>> #dune #dune messiah #dune frank herbert #character arcs

[what-life-im-a-fangirl]

Kady: You really put aside everything and came all this way for me? How did you even get here so fast?

Ezra: Several traffic violations.

Nik: Three counts of resisting arrest.

Ella: Roughly thirteen cans of energy drinks.

Hanna: Also, that is not our car.

AIDAN: I pRoViDeD SiReN nOiSeS.

#incorrect illuminae quotes #the illuminae files #the illuminae group #illuminae #gemina #obsidio #kady grant #ezra mason #hanna donnelly #nik malikov #ella malikova #asha grant #rhys lindstrom #AIDAN #artificial intelligence defense analytics network #jay kristoff #amie kaufman

[in-tenebris-et-in-solitudine]

I pay attention to everything.

#observant #detail-oriented #mindful #aware #present #perceptive #analytical #curious #thoughtful #intelligent #wise #insightful #reflective

[uthra-krish]

From Curious Novice to Data Enthusiast: My Data Science Adventure

I've always been fascinated by data science, a field that seamlessly blends technology, mathematics, and curiosity. In this article, I want to take you on a journey—my journey—from being a curious novice to becoming a passionate data enthusiast. Together, let's explore the thrilling world of data science, and I'll share the steps I took to immerse myself in this captivating realm of knowledge.

The Spark: Discovering the Potential of Data Science

The moment I stumbled upon data science, I felt a spark of inspiration. Witnessing its impact across various industries, from healthcare and finance to marketing and entertainment, I couldn't help but be drawn to this innovative field. The ability to extract critical insights from vast amounts of data and uncover meaningful patterns fascinated me, prompting me to dive deeper into the world of data science.

Laying the Foundation: The Importance of Learning the Basics

To embark on this data science adventure, I quickly realized the importance of building a strong foundation. Learning the basics of statistics, programming, and mathematics became my priority. Understanding statistical concepts and techniques enabled me to make sense of data distributions, correlations, and significance levels. Programming languages like Python and R became essential tools for data manipulation, analysis, and visualization, while a solid grasp of mathematical principles empowered me to create and evaluate predictive models.

The Quest for Knowledge: Exploring Various Data Science Disciplines

A. Machine Learning: Unraveling the Power of Predictive Models

Machine learning, a prominent discipline within data science, captivated me with its ability to unlock the potential of predictive models. I delved into the fundamentals, understanding the underlying algorithms that power these models. Supervised learning, where data with labels is used to train prediction models, and unsupervised learning, which uncovers hidden patterns within unlabeled data, intrigued me. Exploring concepts like regression, classification, clustering, and dimensionality reduction deepened my understanding of this powerful field.

B. Data Visualization: Telling Stories with Data

In my data science journey, I discovered the importance of effectively visualizing data to convey meaningful stories. Navigating through various visualization tools and techniques, such as creating dynamic charts, interactive dashboards, and compelling infographics, allowed me to unlock the hidden narratives within datasets. Visualizations became a medium to communicate complex ideas succinctly, enabling stakeholders to understand insights effortlessly.

C. Big Data: Mastering the Analysis of Vast Amounts of Information

The advent of big data challenged traditional data analysis approaches. To conquer this challenge, I dived into the world of big data, understanding its nuances and exploring techniques for efficient analysis. Uncovering the intricacies of distributed systems, parallel processing, and data storage frameworks empowered me to handle massive volumes of information effectively. With tools like Apache Hadoop and Spark, I was able to mine valuable insights from colossal datasets.

D. Natural Language Processing: Extracting Insights from Textual Data

Textual data surrounds us in the digital age, and the realm of natural language processing fascinated me. I delved into techniques for processing and analyzing unstructured text data, uncovering insights from tweets, customer reviews, news articles, and more. Understanding concepts like sentiment analysis, topic modeling, and named entity recognition allowed me to extract valuable information from written text, revolutionizing industries like sentiment analysis, customer service, and content recommendation systems.

Building the Arsenal: Acquiring Data Science Skills and Tools

Acquiring essential skills and familiarizing myself with relevant tools played a crucial role in my data science journey. Programming languages like Python and R became my companions, enabling me to manipulate, analyze, and model data efficiently. Additionally, I explored popular data science libraries and frameworks such as TensorFlow, Scikit-learn, Pandas, and NumPy, which expedited the development and deployment of machine learning models. The arsenal of skills and tools I accumulated became my assets in the quest for data-driven insights.

The Real-World Challenge: Applying Data Science in Practice

Data science is not just an academic pursuit but rather a practical discipline aimed at solving real-world problems. Throughout my journey, I sought to identify such problems and apply data science methodologies to provide practical solutions. From predicting customer churn to optimizing supply chain logistics, the application of data science proved transformative in various domains. Sharing success stories of leveraging data science in practice inspires others to realize the power of this field.

Cultivating Curiosity: Continuous Learning and Skill Enhancement

Embracing a growth mindset is paramount in the world of data science. The field is rapidly evolving, with new algorithms, techniques, and tools emerging frequently. To stay ahead, it is essential to cultivate curiosity and foster a continuous learning mindset. Keeping abreast of the latest research papers, attending data science conferences, and engaging in data science courses nurtures personal and professional growth. The journey to becoming a data enthusiast is a lifelong pursuit.

Joining the Community: Networking and Collaboration

Being part of the data science community is a catalyst for growth and inspiration. Engaging with like-minded individuals, sharing knowledge, and collaborating on projects enhances the learning experience. Joining online forums, participating in Kaggle competitions, and attending meetups provides opportunities to exchange ideas, solve challenges collectively, and foster invaluable connections within the data science community.

Overcoming Obstacles: Dealing with Common Data Science Challenges

Data science, like any discipline, presents its own set of challenges. From data cleaning and preprocessing to model selection and evaluation, obstacles arise at each stage of the data science pipeline. Strategies and tips to overcome these challenges, such as building reliable pipelines, conducting robust experiments, and leveraging cross-validation techniques, are indispensable in maintaining motivation and achieving success in the data science journey.

Balancing Act: Building a Career in Data Science alongside Other Commitments

For many aspiring data scientists, the pursuit of knowledge and skills must coexist with other commitments, such as full-time jobs and personal responsibilities. Effectively managing time and developing a structured learning plan is crucial in striking a balance. Tips such as identifying pockets of dedicated learning time, breaking down complex concepts into manageable chunks, and seeking mentorships or online communities can empower individuals to navigate the data science journey while juggling other responsibilities.

Ethical Considerations: Navigating the World of Data Responsibly

As data scientists, we must navigate the world of data responsibly, being mindful of the ethical considerations inherent in this field. Safeguarding privacy, addressing bias in algorithms, and ensuring transparency in data-driven decision-making are critical principles. Exploring topics such as algorithmic fairness, data anonymization techniques, and the societal impact of data science encourages responsible and ethical practices in a rapidly evolving digital landscape.

Embarking on a data science adventure from a curious novice to a passionate data enthusiast is an exhilarating and rewarding journey. By laying a foundation of knowledge, exploring various data science disciplines, acquiring essential skills and tools, and engaging in continuous learning, one can conquer challenges, build a successful career, and have a good influence on the data science community. It's a journey that never truly ends, as data continues to evolve and offer exciting opportunities for discovery and innovation. So, join me in your data science adventure, and let the exploration begin!

#data science #data analytics #data visualization #big data #machine learning #artificial intelligence #education #information

[salesmarkglobal]

Data-driven Strategies & Insights in Action by SalesMark Global

At SalesMark Global, we understand that data is only valuable if it can be harnessed. That’s why we offer cutting-edge solutions that help companies structure their data, find insights, and enable intelligence. Our on-demand service delivery ensures you get the information you need, when you need it.

To Learn more B2B Strategies for Analytics Intelligence Visit - 

Also Read- Data-driven Precision Marketing 

#B2B Intent Data #Analytics Intelligence #Data-driven Strategies #data analytics tools #Lead Data Research #Lead Scoring #Customer Profiling #Data Analysis #Data Analytics #B2B Business #B2b Marketing #B2B Strategy #B2B Lead Scoring #B2B Lead Generation #business analytics #account based marketing #artificial intelligence #abm #ai technology #abm strategy #marketing techniques #marketing agency #marketing strategy #data analytics services

[nitor-infotech]

Types of Data Analytics

To get an insight on Data analytics, read here.

#data analysis #data analytics #business analytics #predictive analytics #big data analytics #analytics intelligence #business data analytics #reporting analytics #data analytics companies #data insights

[tilbageidanmark]

Dalle-2

#dalle3 #dalle-2 #analytics #space aesthetic #space art #deep learning #machine learning #bendy and the ink machine #sora #openai #gpt #chatgpt #artificial intelligence #digital artist #digital art #ted chiang #deep fake

[datascienceunicorn]

HT @dataelixir

#data science #data scientist #data scientists #machine learning #analytics #data analytics #artificial intelligence #deep learning #programming #llm #genai

[fangirlingismysport]

Aidan to Kady: Are you alright? You look… not alright.

#incorrect illuminae quotes #illuminae files #aidan illuminae #artificial intelligence defense analytics network