Relevant insights for a manager in India
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This document provides insights for managers on finding a data scientist for their company. It recommends not specifically searching for a data scientist, as a logical person with basic data skills and a creative mindset can help the company more. The person should have basic math, programming, logical thinking, problem-solving abilities and understand key data science principles. Managers should start small with simple problems and focus on people skills rather than exclusively searching for a unicorn data scientist. The overall message is that investing time in the right person can yield better returns than persistently searching for an elusive data scientist.
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Stop searching for that elusive data scientist
The document provides insights for companies on finding a data scientist. It recommends appointing a person with basic data and programming skills rather than searching endlessly for a dedicated data scientist. This person should have strong logical and problem-solving abilities along with a creative mindset. It also stresses keeping problems simple, believing in teamwork, and cultivating a feel for data as an intrinsic part of problem solving in order to improve results.
Analysis of stop searching for that elusive data scientist by michael schrage
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A leader's guide to data analytics
This document discusses the importance for business leaders to have a working knowledge of data analytics. While data science has become essential, many leaders are hesitant to get involved in the technical aspects. The key is for leaders to be able to distinguish good data from bad and understand where analytics can provide value. Leaders should view analytics as integrated into business plans and start by defining the problem. They also need to understand how the data was generated and use their domain knowledge to evaluate results. Managers cannot rely solely on data scientists and ultimately must choose which problems to solve and how to incorporate analytics.
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Generating Business Value thro’ Integrating Data Analysis into planning and...
Data analysis is the lifeline of any business. No business can survive without analyzing available data. Whether one wants to arrive at some marketing decisions or fine-tune new product launch strategy or compute process capability or predicate future trends or breakdown a big issue into smaller but manageable issues; data analysis is the key to all the problems.
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Stop searching for that elusive data scientist
The document provides insights for companies on finding a data scientist. It recommends appointing a person with basic data and programming skills rather than searching endlessly for a dedicated data scientist. This person should have strong logical and problem-solving abilities along with a creative mindset. It also stresses keeping problems simple, believing in teamwork, and cultivating a feel for data as an intrinsic part of problem solving in order to improve results.
Analysis of stop searching for that elusive data scientist by michael schrage
The document summarizes an analysis of the shortage of data scientists. It notes that while large organizations try to hire expensive experts, more prudent enterprises are taking alternate approaches like empowering small cross-functional data teams. These teams should be charged with delivering measurable benefits quickly by building data capabilities rather than infrastructure. The document advises managers to consider metrics that prevent organizational downfalls and to help employees understand data science principles to create a context for future hiring, rather than trying to find a perfect data scientist.
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In order to gain the most from your data and derive meaningful insights, it is important to take a step back. These 4 principles will help you start thinking about data to help you map out where and why you need it, how to structure and manage it, and what to do with it.
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This document provides guidance for managers on effectively using data analytics. It emphasizes that managers should focus on problem solving skills rather than technical skills. The key points are:
1) Managers should link the business problem to the appropriate analytic techniques, and not rely solely on data scientists.
2) Managers need to understand how the data was generated and selected to ensure it is relevant to addressing the problem. Bad data selection can undermine quality analysis.
3) Managers should use their domain expertise to evaluate analytic results and identify plausible business explanations for findings. Analytics alone is not a substitute for understanding the business context.
How to start thinking like a data scientist
This document provides tips for how to start thinking like a data scientist without needing advanced technical skills. It recommends starting with creating a clear question, not getting discouraged from initial failures, doing analysis to address the problem, and repeating the process to find success. The goal is to gain useful insights from data that can help with business decision making and growth.
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This document discusses a learner's guide to data analytics. It outlines several key insights:
1) Business leaders need analytics to make effective decisions and should see it as a thinking skill rather than technical skill.
2) Managers must differentiate between good and bad data analyses by thoroughly understanding problems and how data is generated. They should also question unusual results and know the data themselves.
3) These insights are relevant for Indian managers who must integrate analytics into business plans by starting with a specific problem to solve and ensuring data collection aligns with this problem. Managers should understand data sources and be inquisitive when presented with information.
Stop searching for that elusive data scientist
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"A Leader’s Guide to Data Analytics"
This document discusses the importance for business leaders to have a working knowledge of data science and analytics. It argues that the most important skills in analytics are thinking skills, not technical skills, and that leaders need to understand data generation processes and use their domain expertise when analyzing data. The document provides steps for leaders to develop their understanding, including ensuring analytics starts by addressing specific business problems, understanding how data is generated, using their own knowledge to interpret results, and creating an organizational culture where data and results are questioned.
Stop searching for that elusive data scientist
Small teams of data scientists can generate valuable insights for organizations rather than a single elusive "unicorn" data scientist. The document recommends organizations cultivate internal data science capabilities through small teams who can perform simple but valuable analysis, instead of only hiring external data science experts. It also suggests organizations aim to make all employees more conversant in aligning data, statistics, technology and business value rather than just technical specialists.
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The document discusses how managers can start thinking like data scientists. It emphasizes that data is becoming more important in every industry and managers who are not data savvy will be at a disadvantage. It provides insights on how to start analyzing small data, design questions based on data, visualize answers, and identify gaps to modify data collection. Managers should draw pictures to understand and communicate data, develop summary statistics, understand variation for deeper insights, and continuously ask new questions. The relevance for managers includes conducting primary and complex analysis, sharing insights with data scientists, and identifying talented data scientists to allocate significant tasks.
Analysis of "What People Analytics Can’t Capture" by Daniel Goleman
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A leader’s guide to data analytics
1. The document discusses insights from an article on data analytics leadership. It emphasizes that thinking skills are more important than just technical skills in data analytics.
2. It also notes that just thinking is not enough - one must be able to implement ideas. Developing a culture where people can't get away with just thinking and must know how to implement is a challenge for managers.
3. A manager needs both strong thinking abilities to properly analyze and understand data generation processes, as well as a working knowledge of data science to confidently lead analytics efforts and produce better results.
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2) Managers need to understand how the data was generated and selected to ensure it is relevant to addressing the problem. Bad data selection can undermine quality analysis.
3) Managers should use their domain expertise to evaluate analytic results and identify plausible business explanations for findings. Analytics alone is not a substitute for understanding the business context.
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This document discusses a learner's guide to data analytics. It outlines several key insights:
1) Business leaders need analytics to make effective decisions and should see it as a thinking skill rather than technical skill.
2) Managers must differentiate between good and bad data analyses by thoroughly understanding problems and how data is generated. They should also question unusual results and know the data themselves.
3) These insights are relevant for Indian managers who must integrate analytics into business plans by starting with a specific problem to solve and ensuring data collection aligns with this problem. Managers should understand data sources and be inquisitive when presented with information.
Stop searching for that elusive data scientist
Companies are increasingly seeking data scientists to drive data-based decision making, but there is a lack of qualified candidates. To address this, companies should build effective teams by coordinating existing resources, promoting a data-focused culture, and encouraging all members to contribute insights from available data. Even small groups can draw meaningful conclusions and make informed decisions by maximizing their current capabilities.
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This document discusses both the promises and limitations of using big data analytics to predict job performance. While big data can provide insights, the metrics used may not capture all important factors, and algorithms can make flawed assumptions. Personality tests alone cannot determine who will succeed in a role, and a manager focusing only on short-term targets may hurt the organization long-term. The strongest evaluations come from people familiar with an individual's past performance and behavior over time. Managers should consider statistical analysis carefully alongside other factors to avoid uncertainty and make effective decisions.
What people analytics can’t capture
This document discusses the limitations of people analytics and big data in assessing success and performance. Specifically, it notes that readily available metrics like quarterly targets may not be the most important factors and that the assumptions built into personality tests can discriminate unfairly. The strongest predictor of future behavior is actually past performance, best evaluated by people familiar with an individual, so big data is not necessarily the best judge of performance.
How to Start Thinking Like a Data Scientist
This document summarizes steps for thinking like a data scientist, including posing questions, collecting relevant data, analyzing the data through visualizations and statistics, interpreting the results, and communicating conclusions. It emphasizes that data literacy is important for business managers to effectively collaborate with data scientists and uncover metrics to improve performance. The process of thinking with a data-driven mindset will help managers in India stay competitive as data becomes more integral to decision making across industries.
"A Leader’s Guide to Data Analytics"
This document discusses the importance for business leaders to have a working knowledge of data science and analytics. It argues that the most important skills in analytics are thinking skills, not technical skills, and that leaders need to understand data generation processes and use their domain expertise when analyzing data. The document provides steps for leaders to develop their understanding, including ensuring analytics starts by addressing specific business problems, understanding how data is generated, using their own knowledge to interpret results, and creating an organizational culture where data and results are questioned.
Stop searching for that elusive data scientist
Small teams of data scientists can generate valuable insights for organizations rather than a single elusive "unicorn" data scientist. The document recommends organizations cultivate internal data science capabilities through small teams who can perform simple but valuable analysis, instead of only hiring external data science experts. It also suggests organizations aim to make all employees more conversant in aligning data, statistics, technology and business value rather than just technical specialists.
Analysis of how to start thinking like a data scientist by thomas c. redman
The document discusses how managers can start thinking like data scientists. It emphasizes that data is becoming more important in every industry and managers who are not data savvy will be at a disadvantage. It provides insights on how to start analyzing small data, design questions based on data, visualize answers, and identify gaps to modify data collection. Managers should draw pictures to understand and communicate data, develop summary statistics, understand variation for deeper insights, and continuously ask new questions. The relevance for managers includes conducting primary and complex analysis, sharing insights with data scientists, and identifying talented data scientists to allocate significant tasks.
Analysis of "What People Analytics Can’t Capture" by Daniel Goleman
Daniel Goleman's article discusses the limitations of people analytics and using big data to predict job performance. While data analytics provide benefits, experts caution that the questions being asked and assumptions of algorithms can be flawed. The strongest predictor of future performance is a person's past performance, best evaluated by people familiar with their work. Analytics cannot capture important human qualities like character and interpersonal skills that are difficult to measure.
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Big Data has failed to deliver on its promise because decision-makers and technical practitioners aren't speaking the same language. Cryptic data outputs have to be translated into simple strategy recommendations to turn this trend around.
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Simplify your analytics strategy
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Data Natives Vienna v 7.0 | "The Ingredients of Data Innovation" - Robbert de...
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1. The document discusses insights from an article on data analytics leadership. It emphasizes that thinking skills are more important than just technical skills in data analytics.
2. It also notes that just thinking is not enough - one must be able to implement ideas. Developing a culture where people can't get away with just thinking and must know how to implement is a challenge for managers.
3. A manager needs both strong thinking abilities to properly analyze and understand data generation processes, as well as a working knowledge of data science to confidently lead analytics efforts and produce better results.
Making advanced analytics work for you
this presentation is all about how to have decisions based on your data and how to make customer happy
Identifying And Prototyping Data Science Use Cases
This document discusses best practices for identifying and prototyping data science use cases within an organization. It recommends establishing a process that involves identifying potential use cases by capturing key stakeholder input, evaluating their impact and priority, and developing prototypes to validate feasibility. The document emphasizes an iterative agile process for data science projects that balances scientific exploration with delivering tangible results. It also covers operationalizing and scaling successful prototypes by addressing infrastructure, process, and organizational challenges.
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Analysis of how to start thinking like a data scientist by thomas c. redman
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How to Speak Human - Turning Big Data Insights into Actionable Business Strategy
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One of the most common questions that aspiring data scientists ask is – ‘how do I get a data science job?’ There are many professionals looking to transition to data science but don’t know how. Therefore, this blog explains how you can get a data science job.
What to Know Before Applying
I want to make one thing clear at the start – getting a data science job is not easy. Sure, there are scores of openings and many companies are looking to hire data scientists so that they can gain an edge over their competitors using data.
Design Thinking - In Business Analytics & Big Data
This document discusses design thinking and its application in business analytics and big data. It describes design thinking as a systematic, creative problem-solving methodology. The document outlines the five stages of the design thinking process: discovery, interpretation, ideation, experimentation, and evolution. For each stage, it provides examples of techniques and best practices, such as brainstorming ideas, creating prototypes, seeking user feedback, and continuously improving solutions based on learnings. The overall message is that design thinking can be used to drive innovation by blending business needs, user insights, and technological feasibility.
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Big Data Hype (And Reality)
The document discusses the limitations of using big data to predict human behavior. While big data offers unprecedented insights into consumer actions and attitudes, predicting human behavior remains challenging due to its inconsistency, impulsiveness, and dynamic nature. Marginal gains may be possible through big data analysis, but major breakthroughs are unlikely as long as human behavior remains hard to anticipate. Managers need to thoughtfully apply big data insights and not rely on them exclusively for decision-making, given the inherent randomness in human choices and actions.
The Big Data Revolution In Healthcare
The document discusses the lack of data in healthcare, especially in rural and developing areas, which has led to major disparities between developed and developing countries. Most healthcare data is still collected manually using paper which is inefficient and error-prone. Reliable and high-quality data is needed to accurately understand healthcare issues and solve global problems, but obtaining such data remains a challenge, particularly in places where data is not readily available. Advanced analytics could help predict broader healthcare needs and guide effective responses by analyzing even small, local data samples.
The Big-Data Revolution in Healthcare
The healthcare industry generates huge amounts of data from patients but accessing, managing, and interpreting this data to create useful insights is challenging. Healthcare data is expected to grow from 153 exabytes in 2013 to over 2314 exabytes by 2020, a 48% annual increase. To leverage this data, the industry is transitioning from paper-based data collection to cloud-based systems that can process information faster and provide important insights. Indian healthcare managers should collect data from many sources and use new efficient technologies to analyze the data quickly before it becomes obsolete in order to improve patient care and operational efficiency.
A Leader’s Guide to Data Analytics
The document summarizes key insights from an article on data analytics for leaders. It discusses two main points:
1) Thinking skills are more important than technical skills in data analytics, as data may not always be genuine and thinking is needed to evaluate the data.
2) Thinking alone is not enough; leaders must also know how to implement insights and create an organizational culture where "thinking" is not sufficient without "knowing" and applying skills. A working knowledge of data science helps leaders implement insights with confidence.
Overall, the document argues that a manager with the insights discussed around critical thinking and implementation will be able to achieve better results through data analytics.
3 ways to spot wrong statistics
This document provides 3 questions to consider when evaluating statistics:
1. Can you see uncertainties in the data?
2. Can you see yourself or your experiences represented in the data?
3. How was the data collected? It is important to understand the process used to gather the data as much as the data itself. Proper data collection methods help ensure statistics are trustworthy.
A Predictive Analytics Primer
This document discusses predictive analysis and its key elements. It explains that predictive analysis uses past data to predict the future. The three important elements of quantitative analysis are past data, statistics, and assumptions. It notes that obtaining quality past data at a granular level can be difficult. Regression analysis is commonly used for predictive analysis to find correlations between independent variables. Assumptions help in variable selection, but some Netflix predictive models had to be retired because later internet users were substantially different, invalidating the models' assumptions. The document emphasizes the importance of using the right data, statistical model, and assumptions for accurate predictive analysis.
The best stats you've ever seen
Swedish students scored poorly on a pre-test about global health and development issues. The document argues this was due to preconceived ideas rather than ignorance. It presents animated data visualizations showing trends over time in life expectancy, family size, income distribution, and child mortality across different regions of the world. The visualizations illustrate how countries like China, Latin America, and Africa have changed, with China focusing on better health and Latin America moving towards smaller families. It concludes that such data is not being used efficiently and that animations, interactivity, and search functions are needed to better present information about global trends.
Data is worthless
The document discusses the importance of communicating data effectively. It states that data is worthless if not communicated, and that over 1.5 million managers are needed to take advantage of all generated data. However, results do not speak for themselves, and proper communication is needed. It provides examples of scientists like Gregor Mendel and Dr. John Gottman who achieved recognition through good data communication. While there is data everywhere, it needs to be communicated effectively to the intended audience by focusing only on relevant details. The key message is that having data is not enough - it must be communicated well to have value.
The beauty of Data Visualization
David McCandless creates beautiful data visualizations called infographics that reveal unexpected insights from complex datasets. By turning information like worldwide military spending or Facebook status updates into simple diagrams, McCandless is able to tease out unseen patterns. Good design, he suggests, is the best way to navigate information overload and change how we see the world. The document then provides examples of McCandless' infographics and discusses how visualizing data in this way can provide insights.
Data driven
The document discusses characteristics of being data-driven. Some key characteristics include making decisions at the lowest level using diverse data to develop understanding, appreciating variation, and dealing with uncertainty. The essence of being data-driven is using data to make better decisions throughout an organization. Data-driven individuals conduct experiments, recognize varying decision criteria, realize decisions are not final, and work to improve skills and bring in new data.
More data more human
Jer Thorp argues that data should be made more human by putting people at the center and understanding the context in which data is collected. Visualizing data creatively helps make it more relatable and gives better insights. Managers can use these insights to personalize marketing, understand customer needs in context, and connect more intimately with customers through supportive data visualization. The relationship between people and their data is important, especially regarding privacy.
Big data
Susan Etlinger is an industry analyst who focuses on data and analytics. She has authored two reports on social media ROI and social analytics. She advises clients on measurement strategies and extracting insights from social data. She also works with technology companies to refine their strategies.
Big data refers to very large data sets that cannot be analyzed using traditional techniques. It is characterized by volume, velocity, and variety. Analyzing big data can help solve problems and generate value. The amount of data is growing exponentially from various sources like customer transactions, photos, and genome sequencing. This growth is driving changes in analytics approaches and capabilities.
Data science brings together techniques from computer science, statistics, mathematics, and domain knowledge to extract insights from
Data Scientist
This document discusses data science and data scientists. It defines data science as using scientific methods and processes to extract knowledge and insights from structured and unstructured data. Data scientists are analytical experts who use technical skills and curiosity to solve complex problems by straddling both business and IT. They have skills in mathematics, technology, and business strategy. As data has become more valuable, data scientist roles have evolved from statisticians and analysts to help organizations gain insights from large data sources. Managers should learn to identify data science talent to make their organizations more productive by adding data-driven insights.
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原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样
学校原件一模一样【微信：741003700 】《(Deakin毕业证书)迪肯大学毕业证学位证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
University of New South Wales degree offer diploma Transcript
澳洲UNSW毕业证书制作新南威尔士大学假文凭定制Q微168899991做UNSW留信网教留服认证海牙认证改UNSW成绩单GPA做UNSW假学位证假文凭高仿毕业证申请新南威尔士大学University of New South Wales degree offer diploma Transcript
原版制作(swinburne毕业证书)斯威本科技大学毕业证毕业完成信一模一样
学校原件一模一样【微信：741003700 】《(swinburne毕业证书)斯威本科技大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
毕业原版【微信:41543339】【(爱大毕业证书)爱丁堡大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Natural Language Processing (NLP), RAG and its applications .pptx
1. In the realm of Natural Language Processing (NLP), knowledge-intensive tasks such as question answering, fact verification, and open-domain dialogue generation require the integration of vast and up-to-date information. Traditional neural models, though powerful, struggle with encoding all necessary knowledge within their parameters, leading to limitations in generalization and scalability. The paper "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks" introduces RAG (Retrieval-Augmented Generation), a novel framework that synergizes retrieval mechanisms with generative models, enhancing performance by dynamically incorporating external knowledge during inference.
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
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!
Population Growth in Bataan: The effects of population growth around rural pl...
A population analysis specific to Bataan.
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
学校原件一模一样【微信：741003700 】《(英国UCA毕业证书)创意艺术大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
原版定制【微信:41543339】【(UofS毕业证书)萨省大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
原版定制【微信:41543339】【(Bradford毕业证书)布拉德福德大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Analysis insight about a Flyball dog competition team's performance
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
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
原版定制【微信:41543339】【(BCU毕业证书)伯明翰城市大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(Coventry毕业证书)考文垂大学毕业证如何办理
毕业原版【微信:41543339】【(Coventry毕业证书)考文垂大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
一比一原版(CBU毕业证)卡普顿大学毕业证如何办理
CBU毕业证offer【微信95270640】《卡普顿大学毕业证书》《QQ微信95270640》学位证书电子版：在线制作卡普顿大学毕业证成绩单GPA修改（制作CBU毕业证成绩单CBU文凭证书样本）、卡普顿大学毕业证书与成绩单样本图片、《CBU学历证书学位证书》、卡普顿大学毕业证案例毕业证书制作軟體、在线制作加拿大硕士学历证书真实可查.
如果您是以下情况，我们都能竭诚为您解决实际问题：【公司采用定金+余款的付款流程，以最大化保障您的利益，让您放心无忧】
1、在校期间，因各种原因未能顺利毕业，拿不到官方毕业证+微信95270640
2、面对父母的压力，希望尽快拿到卡普顿大学卡普顿大学毕业证成绩单；
3、不清楚流程以及材料该如何准备卡普顿大学卡普顿大学毕业证成绩单；
4、回国时间很长，忘记办理；
5、回国马上就要找工作，办给用人单位看；
6、企事业单位必须要求办理的；
面向美国乔治城大学毕业留学生提供以下服务:
【★卡普顿大学卡普顿大学毕业证成绩单毕业证、成绩单等全套材料，从防伪到印刷，从水印到钢印烫金，与学校100%相同】
【★真实使馆认证（留学人员回国证明），使馆存档可通过大使馆查询确认】
【★真实教育部认证，教育部存档，教育部留服网站可查】
【★真实留信认证，留信网入库存档，可查卡普顿大学卡普顿大学毕业证成绩单】
我们从事工作十余年的有着丰富经验的业务顾问，熟悉海外各国大学的学制及教育体系，并且以挂科生解决毕业材料不全问题为基础，为客户量身定制1对1方案，未能毕业的回国留学生成功搭建回国顺利发展所需的桥梁。我们一直努力以高品质的教育为起点，以诚信、专业、高效、创新作为一切的行动宗旨，始终把“诚信为主、质量为本、客户第一”作为我们全部工作的出发点和归宿点。同时为海内外留学生提供大学毕业证购买、补办成绩单及各类分数修改等服务；归国认证方面，提供《留信网入库》申请、《国外学历学位认证》申请以及真实学籍办理等服务，帮助众多莘莘学子实现了一个又一个梦想。
专业服务，请勿犹豫联系我
如果您真实毕业回国，对于学历认证无从下手，请联系我，我们免费帮您递交
诚招代理：本公司诚聘当地代理人员，如果你有业余时间，或者你有同学朋友需要，有兴趣就请联系我
你赢我赢，共创双赢
你做代理，可以帮助卡普顿大学同学朋友
你做代理，可以拯救卡普顿大学失足青年
你做代理，可以挽救卡普顿大学一个个人才
你做代理，你将是别人人生卡普顿大学的转折点
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ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
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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查询留服认证是国内鉴别留学生海外学历的唯一途径但认证只是个体行为不是所有留学生都操作所以没有办理认证的留学生的学历在国内也是查询不到的他们也仅仅只有一张文凭。所以这时候我们提供的和学校颁发的一模一样的毕业证成绩单就有了使用价值。只硕大的蛇皮袋手里拎着长铁钩正站在门口朝黑色的屋内张望不好坏人小偷山娃一怔却也灵机一动立马仰起头双手拢在嘴边朝楼上大喊：“爸爸爸——有人找——那人一听朝山娃尴尬地笑笑悻悻地走了山娃立马“嘭的一声将铁门锁死心却咚咚地乱跳当山娃跟父亲说起这事时父亲很吃惊抚摸着山娃的头说还好醒得及时要不家早被人掏空了到时连电视也没得看啰不过父亲还是夸山娃能临危不乱随机应变有胆有谋山娃笑笑说那都是书上学的看童话和小说时多
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Relevant insights for a manager in India
- 1. STOP SEARCHING FOR THAT ELUSIVE DATA SCIENTIST
- 2. HELLO! These Article is written by Michael Schrage. Research Fellow, MIT Center for Digital Business Center for Digital Business. 2
- 3. Insight #01 ● Do not run for finding a Data Scientist for your company. Because a Data Scientist Cannot help your company as much as a normal Logical Person with creative ideas. 3
- 4. Insight #02 ● Instead we have to find a person with basic knowledge of data and make that person work hard on the project you assign. 4
- 5. Insight #03 ● We have to Keep it Simple ● Simple Problem Statement can help to think in new dimensions and hence enhance the system efficiency. ● Adopt the research methodology through analytics to find the relevant solution 5
- 6. The Person You appoint must have following skills: ▰ Basic Mathematical Skills ▰ Basic Programming Skills ▰ High on Logic ▰ Creative Mindset ▰ Problem Solving Approach ▰ Key Principles of Data Science 6
- 7. Relevant Insights For A Manager In India 7
- 8. 1. Start Small, Go Big. ▰ The goal is to make all of the organization-- not just the geeks and quants-- more conversant in how to align probabilty, statistics, technology and business value creation, 8
- 9. 2. People Are People ▰ Data Scientists either produce analytics for machines or humans, but generally not both. ▰ The two types of analysis require different skills. 9
- 10. 3. GIve Up! ▰ Stop Hunting For that Data Scientist unicorn and/or Silver Bullet ▰ Chances are slim that your organization would even be able take full advantage of teirtalent. 10
- 11. “Data Show that ’Buying Time’ Is the right way can be a terrific investment. 1111
- 12. Presented By Prince Barai Data Analyst Intern at IIM, Lucknow 12