Business intelligence (BI) provides tools for exploring, analyzing, and modeling large amounts of complex data. It consists of statistical modeling, data mining, and multidimensional data exploration technologies. BI is built on well-defined data marts and models customer data to provide customer intelligence. It uses several technologies to support decision making, CRM, customer loyalty, campaign management, and marketing. BI requires integrating data from various sources into a data warehouse where advanced analytics can be performed to generate insights.
Retail Webinar - How to Stay 10 Steps Ahead of Retail Competitors?JK Tech
Today, profiling competitors is an imperative strategy. The proactive approach to competitor pricing strategy analysis will assist your retail business to anticipate other competitors’ business strategies. Having such proactive knowledge fosters strategic business agility.
Learn how retail competitive analysis helps you to achieve that competitive edge and optimize your business’s ROI.
Key Takeaways:
1) Monitoring Product Pricing and competitor-tracking.
2) Analytics and insights on competitor pricing & promotions.
3) How to use competitor data to reprice your products at scale?
4) How to detect competitor strategy and avoid the “race to the bottom”?
5) The need to compare the assortment of a brand to competitors in the market.
6) Tracking Manufacturer Suggested Retail Price compliance by resellers.
7) Product mapping using the latest techniques.
8) Also, competition analysis offers many other benefits that you should not miss!
Watch the recorded session here: https://jktech.com/webcast/how-to-stay-10-steps-ahead-of-retail-competitors/
Key Revenue Driving Analyses For Online RetailersDataScience
Are you an online retailer? Does your team have a handful of dashboard tools that display colorful KPI charts but aren't able to answer the questions that drive your business forward? For example, how do we sell a higher volume of our inventory? How do we increase customer retention? How and where do we recommend products to increase sell through rate? The list goes on.
While your dashboard tool isn't able to answer these questions, a data scientist can. We put together a list of key analyses for online retailers as a checklist for certain models that can be applied to identify new revenue opportunities.
The document describes front-door marketing as a specialized form of targeted direct marketing that delivers promotional materials like coupons and samples directly to consumers' front doors. It discusses the benefits of this approach, including its exclusivity and ability to reach consumers in an uncluttered environment. The company described, PowerDirect, offers integrated front-door marketing services including targeted direct mail, real-time personalization, and dynamic testing to improve campaign response and ROI. Case studies show front-door marketing can significantly increase sales, traffic, and redemption rates for major brands.
The document discusses two conversion case histories from AmericanGreetings.com and Moen.com. For AmericanGreetings.com, attribution modeling was used to identify influencers and reallocate budget, leading to a 13% decrease in cost per click, 32% increase in spend, and 28% increase in profit. For Moen.com, guerrilla tactics like timed emails and a product launch sweepstakes were used during a CRM refresh, resulting in a 7% increase in email opens and a 32% increase in response rate. The takeaways emphasize the importance of true analytics over basic metrics, understanding consumer behavior, and creativity during difficult times.
How does MIS at Amazon work - explained in detailbhavindoshi19
Information systems help Amazon grow by optimizing key business functions like customer relationship management, inventory management, supply chain management, finance and accounting, and marketing and sales. These systems provide input data, automate processes, and output actionable insights that help Amazon operate efficiently and make strategic decisions. Looking forward, Amazon will continue leveraging emerging technologies like big data, machine learning, artificial intelligence, and cloud computing to gain deeper insights from massive data streams and provide more personalized customer experiences.
Dynamic surge price and its relation to proactive prediction of supply and de...Nouroz Rahman
This document discusses dynamic pricing and its use in ridesharing platforms. Dynamic pricing, also called surge pricing, involves adjusting prices based on supply and demand in real-time. The biggest challenges for platforms using dynamic pricing are forecasting demand accurately, maximizing revenue through predictive models, and predicting travel times. Machine learning algorithms using large datasets can help address these challenges by improving demand predictions and setting optimal dynamic prices. Joint learning models that combine demand forecasting with revenue-maximizing price optimization show promise for dynamic pricing.
This document contains confidential information belonging to AAUM. Any disclosure of this confidential information to unauthorized third parties could damage AAUM. AAUM retains ownership of all confidential information contained in this document, regardless of the media. The document outlines AAUM's analytics services and provides examples of how various analytics techniques can be applied to solve business problems.
Business intelligence (BI) provides tools for exploring, analyzing, and modeling large amounts of complex data. It consists of statistical modeling, data mining, and multidimensional data exploration technologies. BI is built on well-defined data marts and models customer data to provide customer intelligence. It uses several technologies to support decision making, CRM, customer loyalty, campaign management, and marketing. BI requires integrating data from various sources into a data warehouse where advanced analytics can be performed to generate insights.
Retail Webinar - How to Stay 10 Steps Ahead of Retail Competitors?JK Tech
Today, profiling competitors is an imperative strategy. The proactive approach to competitor pricing strategy analysis will assist your retail business to anticipate other competitors’ business strategies. Having such proactive knowledge fosters strategic business agility.
Learn how retail competitive analysis helps you to achieve that competitive edge and optimize your business’s ROI.
Key Takeaways:
1) Monitoring Product Pricing and competitor-tracking.
2) Analytics and insights on competitor pricing & promotions.
3) How to use competitor data to reprice your products at scale?
4) How to detect competitor strategy and avoid the “race to the bottom”?
5) The need to compare the assortment of a brand to competitors in the market.
6) Tracking Manufacturer Suggested Retail Price compliance by resellers.
7) Product mapping using the latest techniques.
8) Also, competition analysis offers many other benefits that you should not miss!
Watch the recorded session here: https://jktech.com/webcast/how-to-stay-10-steps-ahead-of-retail-competitors/
Key Revenue Driving Analyses For Online RetailersDataScience
Are you an online retailer? Does your team have a handful of dashboard tools that display colorful KPI charts but aren't able to answer the questions that drive your business forward? For example, how do we sell a higher volume of our inventory? How do we increase customer retention? How and where do we recommend products to increase sell through rate? The list goes on.
While your dashboard tool isn't able to answer these questions, a data scientist can. We put together a list of key analyses for online retailers as a checklist for certain models that can be applied to identify new revenue opportunities.
The document describes front-door marketing as a specialized form of targeted direct marketing that delivers promotional materials like coupons and samples directly to consumers' front doors. It discusses the benefits of this approach, including its exclusivity and ability to reach consumers in an uncluttered environment. The company described, PowerDirect, offers integrated front-door marketing services including targeted direct mail, real-time personalization, and dynamic testing to improve campaign response and ROI. Case studies show front-door marketing can significantly increase sales, traffic, and redemption rates for major brands.
The document discusses two conversion case histories from AmericanGreetings.com and Moen.com. For AmericanGreetings.com, attribution modeling was used to identify influencers and reallocate budget, leading to a 13% decrease in cost per click, 32% increase in spend, and 28% increase in profit. For Moen.com, guerrilla tactics like timed emails and a product launch sweepstakes were used during a CRM refresh, resulting in a 7% increase in email opens and a 32% increase in response rate. The takeaways emphasize the importance of true analytics over basic metrics, understanding consumer behavior, and creativity during difficult times.
How does MIS at Amazon work - explained in detailbhavindoshi19
Information systems help Amazon grow by optimizing key business functions like customer relationship management, inventory management, supply chain management, finance and accounting, and marketing and sales. These systems provide input data, automate processes, and output actionable insights that help Amazon operate efficiently and make strategic decisions. Looking forward, Amazon will continue leveraging emerging technologies like big data, machine learning, artificial intelligence, and cloud computing to gain deeper insights from massive data streams and provide more personalized customer experiences.
Dynamic surge price and its relation to proactive prediction of supply and de...Nouroz Rahman
This document discusses dynamic pricing and its use in ridesharing platforms. Dynamic pricing, also called surge pricing, involves adjusting prices based on supply and demand in real-time. The biggest challenges for platforms using dynamic pricing are forecasting demand accurately, maximizing revenue through predictive models, and predicting travel times. Machine learning algorithms using large datasets can help address these challenges by improving demand predictions and setting optimal dynamic prices. Joint learning models that combine demand forecasting with revenue-maximizing price optimization show promise for dynamic pricing.
This document contains confidential information belonging to AAUM. Any disclosure of this confidential information to unauthorized third parties could damage AAUM. AAUM retains ownership of all confidential information contained in this document, regardless of the media. The document outlines AAUM's analytics services and provides examples of how various analytics techniques can be applied to solve business problems.
Learn why the industry’s only comprehensive ABM platform is the bedrock for any ABM strategy. Hear directly from our product team to find out what’s new with the ABM Platform and peek into the future direction. You’ll gain firsthand knowledge and best practices on how leading companies are leveraging the ABM Platform to execute successful ABM programs across the funnel.
American Premium Petroleum is proposing an integrated marketing plan to increase profits by boosting revenue and reducing costs. The plan recommends using a marketing database to track customer purchase history in order to better target promotions, adjust pricing strategies, and identify opportunities for additional sales. Maintaining and updating the database quarterly would allow for analysis of trends to predict future demand and profitability.
Capgemini Smart Analytics Solutions Platform for BankingCapgemini
Capgemini's Smart Analytics Platform for Banking is a powerful platform engine that leverages new technologies and techniques for the ingestion, collation and analysis of customer data.
For more information, please visit:
https://www.capgemini.com/banking-and-capital-markets/capgemini-smart-analytics-solutions
https://www.capgemini.com/insights-data-for-financial-services
Client Profitability: Analysis to ActionPerformLaw
This presentation reviews how law firms can use profitability analysis to understand the basic economics of their practice. With this knowledge, firms have a competitive advantage to make meaningful improvements.
Presentation objectives include:
-Recognize the benefits of client/matter profitability analysis.
- Explain the process for creating a credible profitability analysis.
- Identify the various uses of client profitability.
- Create an action plan for developing a workable client profitability report system.
Introducing ABM Analytics: View Your ABM Results Across the Entire FunnelDemandbase
As technology advances, marketers are constantly seeking deeper and more actionable insights from their solutions. However, their data is often siloed, preventing them from building a holistic view of their marketing results.
With our all-new ABM Analytics, included in the Demandbase ABM Platform, marketers can get a complete picture of their overall marketing performance—across the entire marketing and sales funnel.
Join us for a demo of this new functionality and learn how to:
- Measure and monitor the impact of ABM on your most valued accounts
- Test the effectiveness of your marketing spend with side-by-side comparisons of audiences
- Diagnose challenges in your customer journey, and take action to improve performance
Retail sector can be lauded as oneindustry segment which hasundergone an unprecedentedamount of makeover. Starting fromcattle currency, goods-barter system,metal monies, all the way leading upto paper and then plastic money,digitalcurrencies and e-wallets – theindustry has magnificently evolvedfrom ancient merchant marketplacesto modern day malls andecommerce
platforms.
This document discusses Zensar's CMO Workbench, a data analytics solution that helps retailers improve marketing efforts. The solution uses customer data to segment customers, uncover spending patterns, and target promotional campaigns. This increases campaign ROI, customer retention rates, and revenues from promotional sales. The solution provides dashboards with KPIs, predictive analytics, and visualization tools to optimize marketing mix, measure campaign success, and gain customer insights.
Version5 web analytics- EBTH.com (Everthing But the House)Urooj Ansari
This document discusses user activity data collection and analytics tools used by Everything But The House to maximize profits from online sales. It outlines key metrics such as page views, sessions, unique visitors, time on site, referral traffic, and conversion funnels that are tracked using tools like Google Analytics. The data architecture allows for real-time analytics across channels to optimize marketing goals and drive more seller and buyer traffic, time spent on site, and sales conversions.
B2B Product Sales 101 for Startups : Support deckLuc Boilly
B2B Product Sales 101 for Startups - Long version, aimed as a support deck for a one day workshop.
The overall sales process overview for B2B early stage to market fit Startups .
Enjoy and contact me if you have any questions !
Future of Tracking: Transforming how we do it not what we doKantar
The slides from ‘Digital Transformation of Tracking’ webinar presented on BrightTalk on 28th February 2017. In this webinar Mark Chamberlain and Alex Taylor discuss how changes in consumer behaviour, increased business pressures and new technologies have created both opportunity and disruption across all industries. Like every other industry, research is in the midst of its own transformation affecting not what we do but how we do things.
Elevating customer analytics - how to gain a 720 degree view of your customerActian Corporation
big data creates significant opportunities for marketers. Using big data analytics tools, marketers can improve decision making, deliver better value for their marketing spend, create truly personalized customer experiences, and understand their audience at the level of each individual consumer.
With the proven efficacy of Google Shopping, AdWords text ads are no longer the most profitable way to capitalize on the high-intent shopper queries occurring on Google. Despite this, many brands and retailers still leverage text ads as a key customer acquisition and product advertising channel. So how can text ads – which are used across every single industry and vertical – be optimized for retail conversions?
This 60-minute course features CPC’s Director of Paid Search, David Weichel, discussing how retail advertisers can tweak text ad strategy with automation and different campaign structures to get a better ROI out of the channel.
Topics Discussed Include:
Allowing Shopping Campaign Performance Data to Inform Text Ad Strategy
Structuring Campaigns Based on Brands, Categories, Collections, & Specific SKUs
Applying Automation to Improve Ad Profitability & Ad Copy
Leveraging Remarketing Lists for Search Ads (RLSAs)
15-Minute Live Q&A
Geary LSF University Presents: Advanced AnalyticsKatie Fellenz
Geary LSF University, a Geary LSF Initiative, is proud to present this How-to presentation about Analytics. Learn everything you need to know about analytics and attribution for digital advertising.
Big data analytics can unlock significant potential for retailers to increase operating margins by more than 60% according to a McKinsey report. The document discusses how big data analytics can be applied across customer experience, marketing, merchandizing, and supply chain functions to enhance customer sentiment analysis, optimize product placement and layouts, improve promotional strategies, enable personalized offers, and optimize inventory and warehouse operations. Contact information is provided to discuss business analytics solutions.
Sonocle single customer view platform for dealer groups and OEM's. Unlock the hidden power of your customer data, and supercharge the performance of your dealer marketing.
Three case studies deploying cluster analysisGreg Makowski
Three case studies are discussed, that include cluster analysis as a component.
1) Customer description for a credit card attrition model, to describe how to talk to customers.
2) Hotel price optimization. Use clusters to find subsets of similar behavior, and optimize prices within each cluster. Use a neural net as the objective function.
3) Retail supply chain, planning replenishment using 52 week demand curves using thousands of seasonal "profiles" or clusters.
BRIDGEi2i has frameworks to establish Analytics CoE for Supply Chain functions within organizations. Demand planning solution of BRIDGEi2i aims at using advanced statistical forecasting coupled with real-time decision engines models for demand planning, inventory optimization.
This document discusses Recom Retail Solution, a retail management model centered around manufacturers. It provides customized business intelligence solutions that process and analyze critical business information quickly using tools like artificial intelligence. The solutions help optimize resources, sales, cash flow, and more through dimensional measurement and aggregation. It discusses applications of data mining techniques like market basket analysis, association rules, and clustering to gain insights from customer data.
NetElixir University will share their perspectives on the biggest developments from Google Marketing Live in our third Modern Search Month webinar. You’ll hear their expert takes on:
- Discovery Ads
- Gallery Ads
- New Google Shopping experience
- Other key updates
AUBG Lecture - Data & Analytics - Importance of data.pptxYasen4
Lecture at the American University in Bulgaria talking about the concept of the T-shaped marketer and the importance of data in making informed decisions.
Learn why the industry’s only comprehensive ABM platform is the bedrock for any ABM strategy. Hear directly from our product team to find out what’s new with the ABM Platform and peek into the future direction. You’ll gain firsthand knowledge and best practices on how leading companies are leveraging the ABM Platform to execute successful ABM programs across the funnel.
American Premium Petroleum is proposing an integrated marketing plan to increase profits by boosting revenue and reducing costs. The plan recommends using a marketing database to track customer purchase history in order to better target promotions, adjust pricing strategies, and identify opportunities for additional sales. Maintaining and updating the database quarterly would allow for analysis of trends to predict future demand and profitability.
Capgemini Smart Analytics Solutions Platform for BankingCapgemini
Capgemini's Smart Analytics Platform for Banking is a powerful platform engine that leverages new technologies and techniques for the ingestion, collation and analysis of customer data.
For more information, please visit:
https://www.capgemini.com/banking-and-capital-markets/capgemini-smart-analytics-solutions
https://www.capgemini.com/insights-data-for-financial-services
Client Profitability: Analysis to ActionPerformLaw
This presentation reviews how law firms can use profitability analysis to understand the basic economics of their practice. With this knowledge, firms have a competitive advantage to make meaningful improvements.
Presentation objectives include:
-Recognize the benefits of client/matter profitability analysis.
- Explain the process for creating a credible profitability analysis.
- Identify the various uses of client profitability.
- Create an action plan for developing a workable client profitability report system.
Introducing ABM Analytics: View Your ABM Results Across the Entire FunnelDemandbase
As technology advances, marketers are constantly seeking deeper and more actionable insights from their solutions. However, their data is often siloed, preventing them from building a holistic view of their marketing results.
With our all-new ABM Analytics, included in the Demandbase ABM Platform, marketers can get a complete picture of their overall marketing performance—across the entire marketing and sales funnel.
Join us for a demo of this new functionality and learn how to:
- Measure and monitor the impact of ABM on your most valued accounts
- Test the effectiveness of your marketing spend with side-by-side comparisons of audiences
- Diagnose challenges in your customer journey, and take action to improve performance
Retail sector can be lauded as oneindustry segment which hasundergone an unprecedentedamount of makeover. Starting fromcattle currency, goods-barter system,metal monies, all the way leading upto paper and then plastic money,digitalcurrencies and e-wallets – theindustry has magnificently evolvedfrom ancient merchant marketplacesto modern day malls andecommerce
platforms.
This document discusses Zensar's CMO Workbench, a data analytics solution that helps retailers improve marketing efforts. The solution uses customer data to segment customers, uncover spending patterns, and target promotional campaigns. This increases campaign ROI, customer retention rates, and revenues from promotional sales. The solution provides dashboards with KPIs, predictive analytics, and visualization tools to optimize marketing mix, measure campaign success, and gain customer insights.
Version5 web analytics- EBTH.com (Everthing But the House)Urooj Ansari
This document discusses user activity data collection and analytics tools used by Everything But The House to maximize profits from online sales. It outlines key metrics such as page views, sessions, unique visitors, time on site, referral traffic, and conversion funnels that are tracked using tools like Google Analytics. The data architecture allows for real-time analytics across channels to optimize marketing goals and drive more seller and buyer traffic, time spent on site, and sales conversions.
B2B Product Sales 101 for Startups : Support deckLuc Boilly
B2B Product Sales 101 for Startups - Long version, aimed as a support deck for a one day workshop.
The overall sales process overview for B2B early stage to market fit Startups .
Enjoy and contact me if you have any questions !
Future of Tracking: Transforming how we do it not what we doKantar
The slides from ‘Digital Transformation of Tracking’ webinar presented on BrightTalk on 28th February 2017. In this webinar Mark Chamberlain and Alex Taylor discuss how changes in consumer behaviour, increased business pressures and new technologies have created both opportunity and disruption across all industries. Like every other industry, research is in the midst of its own transformation affecting not what we do but how we do things.
Elevating customer analytics - how to gain a 720 degree view of your customerActian Corporation
big data creates significant opportunities for marketers. Using big data analytics tools, marketers can improve decision making, deliver better value for their marketing spend, create truly personalized customer experiences, and understand their audience at the level of each individual consumer.
With the proven efficacy of Google Shopping, AdWords text ads are no longer the most profitable way to capitalize on the high-intent shopper queries occurring on Google. Despite this, many brands and retailers still leverage text ads as a key customer acquisition and product advertising channel. So how can text ads – which are used across every single industry and vertical – be optimized for retail conversions?
This 60-minute course features CPC’s Director of Paid Search, David Weichel, discussing how retail advertisers can tweak text ad strategy with automation and different campaign structures to get a better ROI out of the channel.
Topics Discussed Include:
Allowing Shopping Campaign Performance Data to Inform Text Ad Strategy
Structuring Campaigns Based on Brands, Categories, Collections, & Specific SKUs
Applying Automation to Improve Ad Profitability & Ad Copy
Leveraging Remarketing Lists for Search Ads (RLSAs)
15-Minute Live Q&A
Geary LSF University Presents: Advanced AnalyticsKatie Fellenz
Geary LSF University, a Geary LSF Initiative, is proud to present this How-to presentation about Analytics. Learn everything you need to know about analytics and attribution for digital advertising.
Big data analytics can unlock significant potential for retailers to increase operating margins by more than 60% according to a McKinsey report. The document discusses how big data analytics can be applied across customer experience, marketing, merchandizing, and supply chain functions to enhance customer sentiment analysis, optimize product placement and layouts, improve promotional strategies, enable personalized offers, and optimize inventory and warehouse operations. Contact information is provided to discuss business analytics solutions.
Sonocle single customer view platform for dealer groups and OEM's. Unlock the hidden power of your customer data, and supercharge the performance of your dealer marketing.
Three case studies deploying cluster analysisGreg Makowski
Three case studies are discussed, that include cluster analysis as a component.
1) Customer description for a credit card attrition model, to describe how to talk to customers.
2) Hotel price optimization. Use clusters to find subsets of similar behavior, and optimize prices within each cluster. Use a neural net as the objective function.
3) Retail supply chain, planning replenishment using 52 week demand curves using thousands of seasonal "profiles" or clusters.
BRIDGEi2i has frameworks to establish Analytics CoE for Supply Chain functions within organizations. Demand planning solution of BRIDGEi2i aims at using advanced statistical forecasting coupled with real-time decision engines models for demand planning, inventory optimization.
This document discusses Recom Retail Solution, a retail management model centered around manufacturers. It provides customized business intelligence solutions that process and analyze critical business information quickly using tools like artificial intelligence. The solutions help optimize resources, sales, cash flow, and more through dimensional measurement and aggregation. It discusses applications of data mining techniques like market basket analysis, association rules, and clustering to gain insights from customer data.
NetElixir University will share their perspectives on the biggest developments from Google Marketing Live in our third Modern Search Month webinar. You’ll hear their expert takes on:
- Discovery Ads
- Gallery Ads
- New Google Shopping experience
- Other key updates
AUBG Lecture - Data & Analytics - Importance of data.pptxYasen4
Lecture at the American University in Bulgaria talking about the concept of the T-shaped marketer and the importance of data in making informed decisions.
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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
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.
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
End-to-end pipeline agility - Berlin Buzzwords 2024Lars Albertsson
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
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Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
Global Situational Awareness of A.I. and where its headed
Ecommerce challenges and analytics solutions
1. USE CASES OF ANALYTICS
E-COMMERCE INDUSTRY CHALLENGES
DATATOBIZ.COM
2. DATATOBIZ.COM
▸ Product Awareness
▸ Advertisement Relevancy
▸ Web-page high bounce rates
ANALYTICAL SOLUTION- ACQUISITION ANALYTICS
▸ ROI driven user target selection
▸ Data centric user acquisition channel selection
▸ CAC vs LTV Analytics
PROBLEM STATEMENT - USER ACQUISITION
3. DATATOBIZ.COM
▸ Customer Loyalty
▸ Brand recall problem
ANALYTICAL SOLUTION - PREDICTIVE CHURN ANALYTICS
▸ Algorithm: Propensity to buy & churn probability prediction for all
users based on RFM (Recency, Frequency, Monetary)
▸ Required Data Points: User id, Purchase Date, Bill amount
▸ Output: User id, Probability to purchase, no. of transactions in specific
time interval (month, trimester, year etc)
▸ Additional data points enhances prediction accuracy
▸ Actionable Data points: Marketing & communication Strategy
PROBLEM STATEMENT - USER RETENTION
4. DATATOBIZ.COM
▸ Delivery trade-of: Business Margins v/s user Satisfaction
▸ Real time Inventory Synchronisation
ANALYTICAL SOLUTION- LOGISTICS ANALYTICS
▸ Real time spatial analytics
▸ Demand Prediction: demand & supply gap reduction
▸ Real time updated communication
PROBLEM STATEMENT - DELIVERY LOGISTICS
5. DATATOBIZ.COM
▸ Reverse logistics & cancellation
▸ Cash management cost
ANALYTICAL SOLUTION- SPATIAL ANALYTICS
▸ Order spatial analytics
▸ Spatial areas identification for COD
▸ Spatial payment strategy
PROBLEM STATEMENT - CASH ON DELIVERY