#DataUsability

[enzo-vupico]

Bridging the Gap Between Data Complexity and Usability for Businesses

Do you use your data to its full potential, or are you being held back by complexity? Nowadays, in a hyper-competitive market, companies are generating and gathering data at an exponential pace. Although this data is a goldmine of information, it is complicated and brings about barriers, many of these organizations are finding it difficult to translate their raw data into actionable strategies. Closing the gap between data complexity and usability is the first step to bringing the transformative growth to light.

Understanding the Data Complexity Dilemma

Modern businesses manage data from diverse sources—customer interactions, IoT devices, financial systems, and more. This heterogeneous combination of well articulated and ill defined data, can be paralyzing, with integration and analysis a challenging problem. If there is no appropriate tool, deep, valuable information stagnates and decisions fail.

Why Data Usability Matters

Usability is the bridge between data and decision-making. It guarantees data is presented in a way that is easily understood, actionable, and applicable to business goals. Decisions are made with speed and efficiency thanks to easy access to insights (visual dashboards, predictive analytics, easy-to-use interfaces) on the business side.

Vupico SDP: Simplifying Data for Better Decisions

Vupico's Smart Data Platform (SDP) is specifically designed to come to grips with the difficulties of data complexity. With a focus on usability, the platform helps businesses:

Centralize and Streamline: To combine data from multiple sources in a single, readily accessible platform.

Democratize Insights: Give teams the means to analyze and act upon data easily.

Increase Efficiency: Automate tedious procedures, creating the fastest path from the data to the decision.

A Call to Action for Leaders

The question is not if your business has enough data, it's not if you've mined data from it. Suspects are equipped with the right tools to handle complexity and turn it into something actionable.

Discover more about the way Vupico SDP can change your approach to data at www.vupico.com.

Resources:

The Usability Factor in Data Analytics

Overcoming the Challenges of Complex Data Systems

How Leading Businesses Build Data-Driven Cultures

© 2024 Vupico SDP. All rights reserved.

[knick-nudiex]

Birds

There are roughly 50 billion birds in the world, though estimates range from 50 billion to 400 billion. 

How do scientists estimate the number of birds?

eBird dataUsed to create accurate censuses of birds in a region, compare abundances, and extrapolate to the global population 

Big dataUsed to analyze actual observations and estimate the number of undocumented birds 

What does the estimate of 50 billion birds mean? 

This estimate is conservative, so the actual number is likely higher

This estimate would mean that there are about six birds for every human

Other bird-related facts

There are over 11,000 species of birds, each with its own unique appearance and habits 

Some bird species are threatened with extinction, while others are abundant 

The house sparrow, European starling, ring-billed gull, and barn swallow are among the most abundant bird species 

[sofiasmartleai]

AI Chatbot Services in E-commerce: Elevating Customer Experience and Driving Growth

In today’s competitive e-commerce landscape, delivering smooth, personalized experiences is essential. One of the most powerful tools enabling this is the AI chatbot. These intelligent virtual assistants enhance customer service, drive engagement, and boost sales. From AI chatbot assistance with routine queries to tailored product suggestions, chatbots are fast becoming a must-have for e-commerce success.

This blog explores the impact of AI chatbots on e-commerce, real-world use cases, key advantages, and common FAQs about AI chatbot services.

The Role of AI Chatbots in E-commerce

Advancements in natural language processing (NLP) and machine learning have transformed AI chatbots into robust tools, allowing brands to interact with customers in real-time. An AI chatbot serves as a digital customer service agent, guiding customers through product discovery, answering queries, and facilitating purchases around the clock.

Benefits include instant responses, reduced operational costs, personalized interactions, and improved customer loyalty. AI chatbots continuously learn from each interaction, becoming smarter and more helpful over time, whether for customer support or sales assistance.

Advantages of AI Chatbots in E-commerce

Round-the-Clock SupportAI chatbots ensure customers can access support at any time, day or night, enhancing the shopping experience without needing extra staffing.

Immediate Responses and Reduced Cart AbandonmentCart abandonment often occurs due to unanswered questions. AI chatbots provide quick responses, helping customers complete purchases and reducing abandonment rates.

Tailored Product RecommendationsAI chatbots analyze customer browsing and purchase history to suggest relevant products, encouraging additional purchases and increasing engagement.

Cost Savings and ScalabilityAutomating routine inquiries minimizes staffing requirements, providing substantial cost savings. AI chatbots can also handle high volumes of interactions, adapting seamlessly to demand.

Multi-channel AssistanceAI chatbots can operate across websites, apps, and social media, offering consistent support across all platforms.

Real-World Examples of AI Chatbot Success in E-commerce

SephoraSephora’s chatbot offers personalized product recommendations and appointment scheduling, making the shopping experience more convenient and strengthening customer loyalty.

H&MH&M’s chatbot on Kik helps users find outfits based on personal style, creating a fun, interactive shopping experience that enhances customer engagement.

eBay’s ShopBotShopBot assists users in finding products by gathering their preferences and budget, simplifying product discovery and supporting informed decisions.

Lego’s RalphRalph, Lego’s chatbot on Messenger, helps users find the perfect Lego set by asking about the recipient’s preferences, making gift-giving easier and improving conversions.

KLM’s BlueBotBlueBot assists customers with flight bookings, boarding passes, and real-time updates, streamlining customer service and allowing agents to handle more complex issues.

Tips for Implementing AI Chatbots in E-commerce

To optimize AI chatbot effectiveness, it’s crucial to understand customer needs, establish clear goals, and choose the right features. Here are some best practices:

Define Specific GoalsDetermine what you want the chatbot to achieve, whether that’s improving customer service, increasing conversions, or offering personalized recommendations.

Focus on Smooth User ExperienceEnsure the chatbot is intuitive and easy to use, allowing users to navigate comfortably and connect with human agents for complex issues.

Personalize with DataUsing customer data allows chatbots to provide tailored responses and suggestions, making the experience more relevant and engaging.

Ensure Multi-Platform AvailabilityMake the chatbot accessible across various platforms, including websites, apps, and social media, for consistent support.

Regularly Update and Monitor PerformanceContinuously review chatbot performance and update it based on user feedback to ensure it aligns with customer expectations.

Frequently Asked Questions About AI Chatbots in E-commerce

1. How do AI chatbots benefit e-commerce?AI chatbots support customer service, answer questions, provide product recommendations, and guide users through the shopping process, reducing cart abandonment and enhancing engagement.

2. How does AI chatbot assistance increase sales?By offering quick responses and personalized recommendations, AI chatbots encourage quicker purchasing decisions and promote upselling and cross-selling.

3. Are AI chatbots useful for small businesses?Yes, AI chatbots are scalable and budget-friendly, making them suitable for small businesses looking to improve customer service without expanding their support teams.

4. What essential features should an e-commerce chatbot have?A strong e-commerce chatbot should handle queries, provide recommendations, assist with checkout, and connect to human agents when needed. Integration with CRM and inventory management is also helpful.

5. Can chatbots handle complex questions?While chatbots manage straightforward inquiries well, complex questions may need human intervention. Advances in AI, however, are enabling chatbots to handle increasingly complex interactions.

The Future of AI Chatbots in E-commerce

The future of AI chatbots in e-commerce looks promising, with improvements in AI, NLP, and machine learning making them more conversational and capable of handling complex queries. Soon, chatbots may become virtual shopping assistants, creating immersive, interactive experiences.

Integration with augmented reality (AR) and virtual reality (VR) is also anticipated, enabling customers to “try on” products virtually. This heightened level of interaction will deepen customer loyalty and make e-commerce even more engaging.

Conclusion: Why AI Chatbots are Crucial for E-commerce Success

AI chatbots are essential for e-commerce brands aiming to stand out in today’s digital market. By using AI chatbot services, businesses can deliver instant, personalized support, reduce operating costs, and enhance the customer journey. Leveraging AI chatbot assistance helps drive higher conversions, increase customer satisfaction, and foster growth.

With a thoughtful strategy, AI chatbots become invaluable for e-commerce, allowing brands to build strong, personalized relationships with customers. As e-commerce evolves, companies that adopt and innovate with AI chatbot technology will lead in customer engagement and satisfaction.

[itfeature-com]

Geometric Mean

Introduction to Geometric Mean The geometric mean (GM) is a way of calculating an average, but instead of adding values like the regular (arithmetic) mean, it multiplies them and then takes a root. The geometric mean is defined as the $n$th root of the product of $n$ positive values. Introduction to Geometric MeanGeometric Mean ExampleGeometric Mean for Grouped DataUse and Application of…

[akshay-s]

TOP 5 APPLICATIONS OF DATA SCIENCE

Whether it’s data, data science, or Data Analysis; all this has been a part of our daily lives. The article lists down the topmost 5 applications of data science from a bunch of other existing applications. Join us @ Great Learning for the Data Science and Analytics Course and become a Data Scientist to know and invent more from it. Now let’s see the impact Data Science is creating and how can we be benefited by using it.

Fraud and Risk Detection

Fraud can come in many forms to you, to me and to each of us either individually or to the industry as a whole. Various techniques are used to get to the bottom of when and why fraud happens. They often use data science/analytics for this purpose. The primary advantage of data analytics is that they can deal with massive quantities of information at once. Through this, they can mark both the normal and abnormal transactions. It doesn’t remove the work done by humans to scrutinize the data and findings but the work is done substantially faster than people could do without help.

Targeted Advertising

Advertising Industry is much much bigger than we think. It is the branch where companies spend lakhs and lakhs of money to stand out from its competitors. But the ultimatum is that they want to spend the smallest amount of money and get the maximum increase in profit. The solution to this is Targeted Advertising. It involves determining where, when, and whom to display a particular advertisement on the Internet. Through this companies can get instant feedback and publishers can receive more knowledge about their users.

Speech Recognition

Google Voice, Siri, Cortana etc. are few of the best examples of speech recognition products. Even if you aren’t in a position to type a message by using speech-recognition your life wouldn’t stop. You just need to speak out the message and it will automatically be converted into text. 

Augmented Reality

Augmented reality (AR) is a simple combination of virtual and real (computer-generated) worlds. Captured on video or camera, the technology 'augments' (= adds to) that real-world image with extra layers of digital information given a real subject. For example: The ability to walk around things and look at Pokemon on walls, streets, things that aren’t really there. 

Gaming

By using data science and its twins in the Gaming Industry the users can get a real-life live 3D experience. The key feature of all types of games is data. You are constantly collecting data while playing a game, knowingly or not, on the current game state and making predictions and decisions based on this data. EA Sports, Sony, Zynga, Activision-Blizzard, Nintendo, have taken the gaming experience to the next level by using data science.

In the end - I would like to conclude that data-science is the backbone of every company now. By using Data Science, companies can arrive at better-decisions although each company has its own requirements. But the ultimate goal is to make businesses grow better.

[techiesblogging]

If you want to know about how much data Netflix uses, then this article is helpful for you in this article you get all information about how much data Netflix uses.

[rajputbalsing]

#CyberSecurity #privacy and #Datause , #Data #Residency and other issues #navbharattimes has covered has issue. Please have a look!!

[growbydata]

GrowByData strongly believe that education, data, and technology can transform individuals, companies, and societies. If we can spark interest amongst students about data and computers and they use these tools for good, we feel proud and it also motivates us.

Our tactical goal is to make teachers digitally literate and familiar with computers, so generations of students would benefit. Team members from different departments, at GrowByData, volunteered to train in this program.

The article is about the part of GrowByData’s ongoing Corporate Social Responsibility Program for 2019.

[eddietechsoln]

Crypto & Blockchain Developers Api Documentation

Crypto & Blockchain Developers Api Documentation

Content Complex Datauseful Market Data Bitcoin Usd Btc Get Deposit Address Zabo’s API reduces integration lead times by up to 80% while consuming a fraction of the engineering resources normally required. With crypto, we’re finally able to show a complete financial picture for our users. Read more about Dragonchain exchange here. Third party explorer URL where the transaction status can be…

[sofiasmartleai]

AI Chatbot Services in E-commerce: Elevating Customer Experience and Driving Growth

In today’s competitive e-commerce landscape, delivering smooth, personalized experiences is essential. One of the most powerful tools enabling this is the AI chatbot. These intelligent virtual assistants enhance customer service, drive engagement, and boost sales. From AI chatbot assistance with routine queries to tailored product suggestions, chatbots are fast becoming a must-have for e-commerce success.

This blog explores the impact of AI chatbots on e-commerce, real-world use cases, key advantages, and common FAQs about AI chatbot services.

The Role of AI Chatbots in E-commerce

Advancements in natural language processing (NLP) and machine learning have transformed AI chatbots into robust tools, allowing brands to interact with customers in real-time. An AI chatbot serves as a digital customer service agent, guiding customers through product discovery, answering queries, and facilitating purchases around the clock.

Benefits include instant responses, reduced operational costs, personalized interactions, and improved customer loyalty. AI chatbots continuously learn from each interaction, becoming smarter and more helpful over time, whether for customer support or sales assistance.

Advantages of AI Chatbots in E-commerce

Round-the-Clock SupportAI chatbots ensure customers can access support at any time, day or night, enhancing the shopping experience without needing extra staffing.

Immediate Responses and Reduced Cart AbandonmentCart abandonment often occurs due to unanswered questions. AI chatbots provide quick responses, helping customers complete purchases and reducing abandonment rates.

Tailored Product RecommendationsAI chatbots analyze customer browsing and purchase history to suggest relevant products, encouraging additional purchases and increasing engagement.

Cost Savings and ScalabilityAutomating routine inquiries minimizes staffing requirements, providing substantial cost savings. AI chatbots can also handle high volumes of interactions, adapting seamlessly to demand.

Multi-channel AssistanceAI chatbots can operate across websites, apps, and social media, offering consistent support across all platforms.

Real-World Examples of AI Chatbot Success in E-commerce

SephoraSephora’s chatbot offers personalized product recommendations and appointment scheduling, making the shopping experience more convenient and strengthening customer loyalty.

H&MH&M’s chatbot on Kik helps users find outfits based on personal style, creating a fun, interactive shopping experience that enhances customer engagement.

eBay’s ShopBotShopBot assists users in finding products by gathering their preferences and budget, simplifying product discovery and supporting informed decisions.

Lego’s RalphRalph, Lego’s chatbot on Messenger, helps users find the perfect Lego set by asking about the recipient’s preferences, making gift-giving easier and improving conversions.

KLM’s BlueBotBlueBot assists customers with flight bookings, boarding passes, and real-time updates, streamlining customer service and allowing agents to handle more complex issues.

Tips for Implementing AI Chatbots in E-commerce

To optimize AI chatbot effectiveness, it’s crucial to understand customer needs, establish clear goals, and choose the right features. Here are some best practices:

Define Specific GoalsDetermine what you want the chatbot to achieve, whether that’s improving customer service, increasing conversions, or offering personalized recommendations.

Focus on Smooth User ExperienceEnsure the chatbot is intuitive and easy to use, allowing users to navigate comfortably and connect with human agents for complex issues.

Personalize with DataUsing customer data allows chatbots to provide tailored responses and suggestions, making the experience more relevant and engaging.

Ensure Multi-Platform AvailabilityMake the chatbot accessible across various platforms, including websites, apps, and social media, for consistent support.

Regularly Update and Monitor PerformanceContinuously review chatbot performance and update it based on user feedback to ensure it aligns with customer expectations.

Frequently Asked Questions About AI Chatbots in E-commerce

1. How do AI chatbots benefit e-commerce?AI chatbots support customer service, answer questions, provide product recommendations, and guide users through the shopping process, reducing cart abandonment and enhancing engagement.

2. How does AI chatbot assistance increase sales?By offering quick responses and personalized recommendations, AI chatbots encourage quicker purchasing decisions and promote upselling and cross-selling.

3. Are AI chatbots useful for small businesses?Yes, AI chatbots are scalable and budget-friendly, making them suitable for small businesses looking to improve customer service without expanding their support teams.

4. What essential features should an e-commerce chatbot have?A strong e-commerce chatbot should handle queries, provide recommendations, assist with checkout, and connect to human agents when needed. Integration with CRM and inventory management is also helpful.

5. Can chatbots handle complex questions?While chatbots manage straightforward inquiries well, complex questions may need human intervention. Advances in AI, however, are enabling chatbots to handle increasingly complex interactions.

The Future of AI Chatbots in E-commerce

The future of AI chatbots in e-commerce looks promising, with improvements in AI, NLP, and machine learning making them more conversational and capable of handling complex queries. Soon, chatbots may become virtual shopping assistants, creating immersive, interactive experiences.

Integration with augmented reality (AR) and virtual reality (VR) is also anticipated, enabling customers to “try on” products virtually. This heightened level of interaction will deepen customer loyalty and make e-commerce even more engaging.

Conclusion: Why AI Chatbots are Crucial for E-commerce Success

AI chatbots are essential for e-commerce brands aiming to stand out in today’s digital market. By using AI chatbot services, businesses can deliver instant, personalized support, reduce operating costs, and enhance the customer journey. Leveraging AI chatbot assistance helps drive higher conversions, increase customer satisfaction, and foster growth.

With a thoughtful strategy, AI chatbots become invaluable for e-commerce, allowing brands to build strong, personalized relationships with customers. As e-commerce evolves, companies that adopt and innovate with AI chatbot technology will lead in customer engagement and satisfaction.

[winportables]

Portable Cloud eXplorer Forensic is a convenient tool for downloading, viewing, and analyzing the data available in a user's Google account. The product will help you access data such as users' contacts and social circle, search history, Google Keep notes, Hangouts messages, browsing history and synchronized Chrome browser bookmarks, as well as data about the user's location. and stored in Google. Photos in the cloud. Main features: Download a complete Google account data set with one clickLocation history, search queries and visits, passwords and user correspondenceSupport for accounts protected by two-factor authenticationThe ability to log into an account without a password and bypass two-factor authenticationSignificantly more data is retrieved compared to Google TakeoutFiles are downloaded from Google Drive cloud storageIntegrated search and filter functionsElcomsoft Cloud Explorer retrieves the following types of data: User profile and related informationFiles and documents in Google Drive storageGmail correspondence (accessed through the Gmail API)Wireless Wi-Fi information (SSID and passwords)Hangout messagesSMS (for phones running Android 8 Oreo and also for Google Pixel, Pixel XL running Android 7 or higher)User call logContacts (including mobile device contacts)Google Keep NotesSearch query history, including history of clicks on links foundGoogle Chrome browser data, including bookmarks, passwords, and saved web form data. [1]Photos and videos saved in the Google Photos cloud service (including EXIF)All calendars availabledashboard dataUser location history, including data from all mobile devices registered to the investigated accountAdditional cartographic data and routes with reference to objects on the map.Some data from Android mobile devices 7/8/8.1/10English61.3MB 

[goodorbetterprogrammer]

HackingWithSwift Day 13

Review basic Part 1

Variables and constant

If you know that you are not going to or not suppose to change the value of a variable , it’s best to declare it as constant so when you try to change it, Xcode will throw error. In a way, it’s a safe guard. =======================

Types of Data

User can choose to explicitly define the type annotation or let swift decide it, also known as type inference.

For example

let score = 20.0 is the same as

let score : Double score = 20.0

Float vs Double As for which one to use, it depends on how big the number you want to store

var longitude: Float longitude = -86.783333 //78333 longitude = -186.783333 //7833 longitude = -1286.783333 //783 longitude = -12386.783333 //78 longitude = -123486.783333 //8 longitude = -1234586.783333 //no more faction

Since Float has limited space, it prioritise round number first, then only do the fraction number. If you change it to Double, then no issue at all

Boolean - probably gonna skip this one since it’s pretty straight forward

====================

Operators

+ , - , / , * , = , %

Those are the basic operators, then there’s the -=, +=.

Then follow by “Comparison Operators”

> , < , >= , <= , == , !=

=====================

String interpolation

“This is a fancy name for what is actually a very simple thing: combining variables and constants inside a string.” I like this definition by the author, haha. “Fancy Name”

var name = "Tim McGraw" var age = 25 var latitude = 36.166667

"Your name is \(name), your age is \(age), and your latitude is \(latitude)"

The “\()” is the key. For sure we can do it with “+” as well, but that’s only applicable when you try combine with string only. If string + Int or other data type, it will not work.

========================

Arrays

var evenNumbers = [2, 4, 6, 8] var songs = ["Shake it Off", "You Belong with Me", "Back to December"]

With type inference, swift know that evenNumbers is an array of Int, and songs is an array of String

To know the actual type of the array, you can print type(of: songs) , then you will see the data type.

var songs = ["Shake it Off", "You Belong with Me", "Back to December", 3]

Swift will throw error since type inference can’t handle mixed data type, and to explicitly define it, you can use [Any] , means it accept any kind of data. But this is not a good practice as it will involve a lot of unwrapping to do to confirm the data type before assign to a variable or constant

And how to create an empty array? There are 2 choices

var songs: [String] = [] var songs = [String]()

And there’s operator for array as well

var songs = ["Shake it Off", "You Belong with Me", "Love Story"] var songs2 = ["Today was a Fairytale", "Welcome to New York", "Fifteen"] var both = songs + songs2 both += ["Everything has Changed"]

+= will work, but -= won’t work in this case so must take note.

=========================

Dictionaries

var person = ["Taylor", "Alison", "Swift", "December", "taylorswift.com"]

If we store a person info in an array, we won’t know how to get the data easily as all the data go by index.

var person = ["first": "Taylor", "middle": "Alison", "last": "Swift", "month": "December", "website": "taylorswift.com"]

If we change to dictionary, value can be retrieve by key, such as person[“first”]. Both array and dictionaries also required an identifier to obtain the value BUT, one of them is index, the other one is key, for the key, we can label it with something more meaningful and easier to remember, compare to index, which is 0,1,2,3,4,5

=========================

Conditional statements

Basically is “if”, “else” , “if else”.

And a few operators, “==” , “||” , “&&” , “!” (NOT)

==========================

Loops

Standard For loops, with … , ..< and _ (underscore) when value not needed

for i in 1...10 {    print("\(i) x 10 is \(i * 10)") }

for i in 1..<10 {    print("\(i) x 10 is \(i * 10)") }

for _ in 1 ... 5 {    str += " fake" }

Sample for looping an array

var songs = ["Shake it Off", "You Belong with Me", "Look What You Made Me Do"]

for song in songs {    print("My favorite song is \(song)") }

For loop in a for loop var people = ["players", "haters", "heart-breakers", "fakers"] var actions = ["play", "hate", "break", "fake"]

for i in 0 ..< people.count {    var str = "\(people[i]) gonna"

   for _ in 1 ... 5 {        str += " \(actions[i])"    }

   print(str) }

Then there’s the “while” , “do while” , and “break” , along with for loop labelling to break a few nested loop at the same time.

======================

Switch case

let liveAlbums = 2

switch liveAlbums { case 0:    print("You're just starting out")

case 1:    print("You just released iTunes Live From SoHo")

case 2:    print("You just released Speak Now World Tour")

default:    print("Have you done something new?") }

Nothing much to explain for this. Straight forward

[towardsai]

Sentiment Analysis with Logistic Regression Author(s): Buse Yaren Tekin Natural Language ProcessingPhoto by Markus Spiske on Unsplash📌 Logistic Regression is a classification that serves to solve the binary classification problem. The result is usually defined as 0 or 1 in the models with a double situation.Image by Wikipedia [1]🩸Estimation is made by applying binary classification with Logistic Regression on the data allocated to training and test data in a data set below. First of all, Standardization for pre-processing will be applied, then training data will be trained with fit( ) and then it will be used to estimate test data with the predict( ) method.Training of training dataUsing test data to predictWhat is Sentiment Analysis with Logistic #MachineLearning #ML #ArtificialIntelligence #AI #DataScience #DeepLearning #Technology #Programming #News #Research #MLOps #EnterpriseAI #TowardsAI #Coding #Programming #Dev #SoftwareEngineering https://bit.ly/3lkzNfV #naturallanguageprocessing

[exactlyloudcollector]

The Next-Generation Cloud Data Lake

Simply moving an on-prem data lake to the cloud doesn’t make it “modern.” Check out this ebook to learn why only the cloud data lakes that make complex data easily accessible and complex queries highly performant to a wide range of data users.

Read More:-  https://www.hqpubs.net/the-next-generation-cloud-data-lake-2/

#cloud #cloudcomputing #data #ebook #complex #dataprocessing #datauser

[fufupaw]

Assess community assignment please use all the information I send it used the we

Assess community assignment please use all the information I send it used the we

Assess community assignment please use all the information I send it used the webside Datausa to explore datause will give you all the informations.My community will be Coral springs florida,you need to put the population value of the propriety,on Datausa copy and pace on 2 para graph of parapoint,3 paragrapph.click on sleeping tool window look for are to copy/pace on 3 para graph ,look at the…