Making advanced analytics work for you
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Big data and analytics have become top priorities for companies but most are unsure how to utilize them effectively. The document recommends that companies first identify and combine multiple data sources, build advanced analytics models to predict and optimize outcomes, and transform their organizational capabilities so data and models can improve decision-making.
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Making advanced analytics work for you
Big data and analytics have become top priorities for companies. To fully leverage data, companies need the ability to collect and manage multiple data sources, build advanced analytics models, and transform their organization to make better decisions using data and models. While skepticism exists, companies that learn core big data skills may gain a competitive advantage, as these capabilities become more important for competition.
Making advanced analytics work for you.
Big data and analytics have rocketed to the top of the corporate agenda. Executives look with admiration at how Google, Amazon, and others have eclipsed competitors with powerful new business models that derive from an ability to exploit data.
Making advanced analytics work for you
This is a qualitative analysis of an article titled "Making Advanced Analytics Work for You" by Dominic Barton and David Court
Making advanced analytics work for you
This presentation explains the article "making advanced analytics work for you" by Dominic Barton and David Court
Making advanced analytics work for you
Big data and analytics is becoming increasingly important for corporations. Many top companies like Google and Amazon use business models fueled by big data to gain a competitive advantage. Research also shows companies that effectively use big data have productivity and profitability rates 5-6% higher than peers. However, some leaders are still cautious about using big data, due to inability to fully utilize existing analytics programs or prior experiences not meeting expectations. To successfully use big data, organizations need three key capabilities: collecting and managing multiple data sources, building advanced analytics models, and transforming the organization so data and models can improve decision making.
Analysis of making advanced analytics work for you by jyotsana manglani
The document discusses how companies can make advanced analytics work for them by focusing on three key capabilities: choosing the right data, building models that predict and optimize business outcomes, and transforming company capabilities. It notes that companies using big data and analytics show 5-6% higher productivity and profits than peers. However, many initial implementations fail because they are not aligned with day-to-day processes and decision-making. The document recommends that companies source data creatively to solve specific problems, build simple models that improve performance, and help managers view analytics as central to problem-solving.
Making Advanced Analytics Work for You
1. Advanced analytics has become a top priority for companies and a trendy job field, but many struggle with how to implement it effectively.
2. While some companies see a 5-6% increase in productivity and profits through analytics, others face challenges like not knowing how to use their data, inability to gain useful insights, and added complexity.
3. To make analytics work, companies need to identify and combine multiple data sources, build models to predict outcomes, and transform their organization to better utilize insights through strategic changes.
Making advance analytics work for you
The document discusses how companies can make advanced analytics work for them. It states that companies that effectively use big data and analytics show 5-6% higher productivity and profitability. It advocates defining a pragmatic approach focused on using data to make better decisions. This requires identifying and managing multiple data sources, building models to predict and optimize outcomes, and transforming the organization so data and models yield better decisions. It provides three steps to discover the purpose of data and convert it into action: choose the right data, build models that predict and optimize business outcomes, and transform company capabilities to develop analytics and exploit big data. The desired business impact must drive an integrated approach to data, modeling, and organizational transformation.
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Making advanced analytics work for you
Big data and analytics have become top priorities for companies. To fully leverage data, companies need the ability to collect and manage multiple data sources, build advanced analytics models, and transform their organization to make better decisions using data and models. While skepticism exists, companies that learn core big data skills may gain a competitive advantage, as these capabilities become more important for competition.
Making advanced analytics work for you.
Big data and analytics have rocketed to the top of the corporate agenda. Executives look with admiration at how Google, Amazon, and others have eclipsed competitors with powerful new business models that derive from an ability to exploit data.
Making advanced analytics work for you
This is a qualitative analysis of an article titled "Making Advanced Analytics Work for You" by Dominic Barton and David Court
Making advanced analytics work for you
This presentation explains the article "making advanced analytics work for you" by Dominic Barton and David Court
Making advanced analytics work for you
Big data and analytics is becoming increasingly important for corporations. Many top companies like Google and Amazon use business models fueled by big data to gain a competitive advantage. Research also shows companies that effectively use big data have productivity and profitability rates 5-6% higher than peers. However, some leaders are still cautious about using big data, due to inability to fully utilize existing analytics programs or prior experiences not meeting expectations. To successfully use big data, organizations need three key capabilities: collecting and managing multiple data sources, building advanced analytics models, and transforming the organization so data and models can improve decision making.
Analysis of making advanced analytics work for you by jyotsana manglani
The document discusses how companies can make advanced analytics work for them by focusing on three key capabilities: choosing the right data, building models that predict and optimize business outcomes, and transforming company capabilities. It notes that companies using big data and analytics show 5-6% higher productivity and profits than peers. However, many initial implementations fail because they are not aligned with day-to-day processes and decision-making. The document recommends that companies source data creatively to solve specific problems, build simple models that improve performance, and help managers view analytics as central to problem-solving.
Making Advanced Analytics Work for You
1. Advanced analytics has become a top priority for companies and a trendy job field, but many struggle with how to implement it effectively.
2. While some companies see a 5-6% increase in productivity and profits through analytics, others face challenges like not knowing how to use their data, inability to gain useful insights, and added complexity.
3. To make analytics work, companies need to identify and combine multiple data sources, build models to predict outcomes, and transform their organization to better utilize insights through strategic changes.
Making advance analytics work for you
The document discusses how companies can make advanced analytics work for them. It states that companies that effectively use big data and analytics show 5-6% higher productivity and profitability. It advocates defining a pragmatic approach focused on using data to make better decisions. This requires identifying and managing multiple data sources, building models to predict and optimize outcomes, and transforming the organization so data and models yield better decisions. It provides three steps to discover the purpose of data and convert it into action: choose the right data, build models that predict and optimize business outcomes, and transform company capabilities to develop analytics and exploit big data. The desired business impact must drive an integrated approach to data, modeling, and organizational transformation.
Making analytics work
Big data has transformed many businesses, though some companies remain wary of investing heavily in it. To successfully use analytics, companies must follow three steps: source and manage multiple data sources, build advanced analytics models to predict and optimize outcomes, and transform the organization so data and models guide better decisions. Specifically, companies should identify usable existing data and new sources, develop simple yet powerful analytics tools, and train employees to make data-driven decisions. When done right, analytics can optimize performance if grounded in business needs and practical data relationships.
Making advanced analytics work for you
This document discusses how companies can benefit from big data and analytics. It states that companies using big data and analytics show 5-6% higher productivity and profitability. To benefit, companies must identify and manage multiple data sources, build advanced analytics models, and transform their organization to make better decisions based on data and models. This requires a clear strategy for competing with data and the right technology. The challenges include choosing the right data, building models that optimize outcomes, and transforming capabilities so managers understand and trust models.
Making analytics work for you
The document discusses how companies can fully harness the power of data analytics. It provides two key insights: 1) Companies must choose the right data, build predictive models, and transform capabilities. 2) They should develop business-relevant analytics, embed analytics in simple tools, and develop big data skills. The insights emphasize upgrading managerial analytics skills so decision-making is data-driven. Acting on these insights can help Indian managers lead a successful digital transformation.
Making advanced analytics work for you
Companies that utilize big data and analytics show productivity and profitability rates 5-6% higher than peers. Leaders should invest time to align managers across the organization behind using multiple data sources to build advanced analytical models, develop capabilities for exploiting big data, and create business-relevant analytics in order to transform capabilities. Data-driven strategies, when successfully implemented, can become an important competitive differentiator.
Making Advanced Analytics Work for You by Dominic Barton and David Court
Organizations need to develop three key capabilities to make advanced analytics work for them: (1) choose the right data to analyze; (2) build models that can predict outcomes and optimize business performance; and (3) transform their company's culture and capabilities to support data-driven decision making through training, leadership, incentives, and metrics. Developing these mutually supportive capabilities will help companies gain competitive advantages from their data and analytics strategies.
Making advanced analytics work for you
Presentation by Sheyas Jadhav on the article "Making Advanced Analytics Work for You" by Dominic Barton and David Court.
DSA Presentation 4
1. The document discusses how companies can make advanced analytics work for them by following three steps: choosing the right data, building models that predict and optimize outcomes, and transforming the company's capabilities.
2. It emphasizes that companies first need to identify business problems and opportunities, source data creatively around those issues, and get necessary IT support. Models should be built with the goal of improving performance, not just analyzing data.
3. Transforming capabilities requires developing business-relevant analytics, embedding analytics into simple tools for managers, and developing analytical skills across the organization so data-driven insights can permeate decision making.
Managerial insights on article - "Making Advanced Analytics Work for You"
Managerial insights on article - "Making Advanced Analytics Work for You"Potlacheruvu Sai Krishna Vamsi
These are my insights on the article "Making Advanced Analytics Work for You" by Dominic Barton and David Court. This is an assignment, part of data analytics internshipMaking advanced analytics work for you
Big data could transform the way companies do business, delivering performance gains. How to get the strategy suited to your needs?
Making advanced analytics work for you
This document discusses how companies can make advanced analytics work for them by developing three key capabilities: 1) Choosing the right data sources creatively and getting necessary IT support, 2) Building models that predict and optimize business outcomes by focusing on business opportunities, and 3) Transforming company capabilities by developing business-relevant analytics, embedding them into front-line tools, and developing analytical skills. Fully exploiting data and analytics requires developing all three of these mutually supportive capabilities.
Creating a Data-Driven Organization (Data Day Seattle 2015)
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The document discusses how to create a data-driven organization. It argues that being data-driven requires having strong analytics, a data-focused culture, and using data to drive impact and business results. Some key aspects of a data-driven culture discussed are having a testing mindset, open data sharing, self-service analytics access for business units, broad data literacy, and visible data leadership. The presentation provides examples of actions organizations can take to promote a data-driven culture, such as improving analyst competencies and linking metrics to strategic goals. It cautions that becoming complacent once progress is made can undermine data-driven efforts, as demonstrated by Tesco's experience.
How unused Big Data turns into Big Value
In all areas of enterprise, teams and departments are looking for actionable data. There are endless benefits to managing Big Data instead of either ignoring it or allowing it to outpace your organization. Many organizations either discard or ignore terabytes of data about customers, operations, and revenue opportunities.
You may not need big data after all
While companies are investing heavily in data analytics technologies, many are not seeing significant returns because they lack the capabilities to properly analyze data and implement changes based on insights. For businesses to truly benefit from big data, managers must focus first on using data to guide operational decisions, establish processes for cleaning and analyzing data, and drive cultural changes to support evidence-based decision making. Only after achieving these foundations can companies hope to leverage more advanced big data technologies and analytics to gain competitive advantages.
Stop Searching for That Elusive Data Scientist
The document discusses finding data scientists for organizations. It recommends that organizations find people within who have basic logical and data skills, rather than trying to hire "unicorns". It also suggests that organizations form small, cross-functional teams focused on delivering measurable benefits from data in short periods to build data capabilities. These teams may be less skilled than a single data scientist but learn from each other and show what can be achieved with data. The document stresses the importance of understanding data science principles to ask the right questions of data and help managers predict outcomes.
Presentation4
According to research, companies that effectively use big data and analytics show 5-6% higher productivity and profitability than their peers. To do this requires three capabilities: identifying and managing multiple data sources, building advanced analytics models, and transforming the organization so data and models improve decisions. The document provides recommendations for choosing usable data sources, establishing supportive IT infrastructure, building models to optimize business outcomes, and transforming company capabilities to develop and utilize analytics. Overall, developing capabilities around big data may become a key competitive advantage.
Data Science Analytics And Information Part 7
Data analytics is more specific and concentrated than data science. Data analytics focuses more on viewing the historical data in context while data science focuses more on machine learning and predictive modeling.
VISIT: https://datamites.com/data-science-course-training-hyderabad/
An analysis of Making Advanced Analytics Work for You by Dominic Barton and D...
This document discusses how companies can make advanced analytics work for them. It outlines that fully exploiting data and analytics requires three capabilities: identifying and managing multiple data sources, building advanced analytics models, and transforming the organization so data and models yield better decisions. Two key features are having a clear strategy for how to use data/analytics to compete and deploying the right technology. The document provides three areas of action for organizational change: developing business-relevant analytics, embedding analytics into front-line tools, and developing capabilities to exploit big data. Managers need to understand how information can be used for key decisions and get creative about potential external/new data sources through targeted efforts.
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.
Making advanced analytics work for you
The document discusses how companies can make advanced analytics work for them by overcoming problems and fully exploiting data. It recommends that companies 1) identify multiple data sources and manage the data, 2) build advanced analytics models, and 3) transform their organization. It also stresses having a clear data strategy and the right technology. Managers are advised to develop business analytics, embed tools for front lines, and build big data capabilities.
Making advanced analytics work for you
The document discusses making advanced analytics work for companies. It provides guidance on choosing the right data, building models that predict and optimize business outcomes, and transforming a company's capabilities. It emphasizes starting with identifying a business opportunity and determining how analytics can improve performance. While big data can solve companies' problems, organizational change is needed to fully exploit analytics capabilities. Research shows companies using big data and analytics have 5-6% higher productivity and profitability than their peers.
Advanced analytics
The document discusses how companies can make advanced analytics work for them using big data. It recommends that companies identify trustworthy sources to collect data, develop capabilities to build advanced analytics models to predict and optimize outcomes from the collected data. It also stresses that companies must help decision makers understand how data insights align with business processes and decision-making norms so they can be implemented smoothly to provide a competitive edge over others and increase profits.
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
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Making analytics work
Big data has transformed many businesses, though some companies remain wary of investing heavily in it. To successfully use analytics, companies must follow three steps: source and manage multiple data sources, build advanced analytics models to predict and optimize outcomes, and transform the organization so data and models guide better decisions. Specifically, companies should identify usable existing data and new sources, develop simple yet powerful analytics tools, and train employees to make data-driven decisions. When done right, analytics can optimize performance if grounded in business needs and practical data relationships.
Making advanced analytics work for you
This document discusses how companies can benefit from big data and analytics. It states that companies using big data and analytics show 5-6% higher productivity and profitability. To benefit, companies must identify and manage multiple data sources, build advanced analytics models, and transform their organization to make better decisions based on data and models. This requires a clear strategy for competing with data and the right technology. The challenges include choosing the right data, building models that optimize outcomes, and transforming capabilities so managers understand and trust models.
Making analytics work for you
The document discusses how companies can fully harness the power of data analytics. It provides two key insights: 1) Companies must choose the right data, build predictive models, and transform capabilities. 2) They should develop business-relevant analytics, embed analytics in simple tools, and develop big data skills. The insights emphasize upgrading managerial analytics skills so decision-making is data-driven. Acting on these insights can help Indian managers lead a successful digital transformation.
Making advanced analytics work for you
Companies that utilize big data and analytics show productivity and profitability rates 5-6% higher than peers. Leaders should invest time to align managers across the organization behind using multiple data sources to build advanced analytical models, develop capabilities for exploiting big data, and create business-relevant analytics in order to transform capabilities. Data-driven strategies, when successfully implemented, can become an important competitive differentiator.
Making Advanced Analytics Work for You by Dominic Barton and David Court
Organizations need to develop three key capabilities to make advanced analytics work for them: (1) choose the right data to analyze; (2) build models that can predict outcomes and optimize business performance; and (3) transform their company's culture and capabilities to support data-driven decision making through training, leadership, incentives, and metrics. Developing these mutually supportive capabilities will help companies gain competitive advantages from their data and analytics strategies.
Making advanced analytics work for you
Presentation by Sheyas Jadhav on the article "Making Advanced Analytics Work for You" by Dominic Barton and David Court.
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1. The document discusses how companies can make advanced analytics work for them by following three steps: choosing the right data, building models that predict and optimize outcomes, and transforming the company's capabilities.
2. It emphasizes that companies first need to identify business problems and opportunities, source data creatively around those issues, and get necessary IT support. Models should be built with the goal of improving performance, not just analyzing data.
3. Transforming capabilities requires developing business-relevant analytics, embedding analytics into simple tools for managers, and developing analytical skills across the organization so data-driven insights can permeate decision making.
Managerial insights on article - "Making Advanced Analytics Work for You"
Managerial insights on article - "Making Advanced Analytics Work for You"Potlacheruvu Sai Krishna Vamsi
These are my insights on the article "Making Advanced Analytics Work for You" by Dominic Barton and David Court. This is an assignment, part of data analytics internshipMaking advanced analytics work for you
Big data could transform the way companies do business, delivering performance gains. How to get the strategy suited to your needs?
Making advanced analytics work for you
This document discusses how companies can make advanced analytics work for them by developing three key capabilities: 1) Choosing the right data sources creatively and getting necessary IT support, 2) Building models that predict and optimize business outcomes by focusing on business opportunities, and 3) Transforming company capabilities by developing business-relevant analytics, embedding them into front-line tools, and developing analytical skills. Fully exploiting data and analytics requires developing all three of these mutually supportive capabilities.
Creating a Data-Driven Organization (Data Day Seattle 2015)
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The document discusses how to create a data-driven organization. It argues that being data-driven requires having strong analytics, a data-focused culture, and using data to drive impact and business results. Some key aspects of a data-driven culture discussed are having a testing mindset, open data sharing, self-service analytics access for business units, broad data literacy, and visible data leadership. The presentation provides examples of actions organizations can take to promote a data-driven culture, such as improving analyst competencies and linking metrics to strategic goals. It cautions that becoming complacent once progress is made can undermine data-driven efforts, as demonstrated by Tesco's experience.
How unused Big Data turns into Big Value
In all areas of enterprise, teams and departments are looking for actionable data. There are endless benefits to managing Big Data instead of either ignoring it or allowing it to outpace your organization. Many organizations either discard or ignore terabytes of data about customers, operations, and revenue opportunities.
You may not need big data after all
While companies are investing heavily in data analytics technologies, many are not seeing significant returns because they lack the capabilities to properly analyze data and implement changes based on insights. For businesses to truly benefit from big data, managers must focus first on using data to guide operational decisions, establish processes for cleaning and analyzing data, and drive cultural changes to support evidence-based decision making. Only after achieving these foundations can companies hope to leverage more advanced big data technologies and analytics to gain competitive advantages.
Stop Searching for That Elusive Data Scientist
The document discusses finding data scientists for organizations. It recommends that organizations find people within who have basic logical and data skills, rather than trying to hire "unicorns". It also suggests that organizations form small, cross-functional teams focused on delivering measurable benefits from data in short periods to build data capabilities. These teams may be less skilled than a single data scientist but learn from each other and show what can be achieved with data. The document stresses the importance of understanding data science principles to ask the right questions of data and help managers predict outcomes.
Presentation4
According to research, companies that effectively use big data and analytics show 5-6% higher productivity and profitability than their peers. To do this requires three capabilities: identifying and managing multiple data sources, building advanced analytics models, and transforming the organization so data and models improve decisions. The document provides recommendations for choosing usable data sources, establishing supportive IT infrastructure, building models to optimize business outcomes, and transforming company capabilities to develop and utilize analytics. Overall, developing capabilities around big data may become a key competitive advantage.
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VISIT: https://datamites.com/data-science-course-training-hyderabad/
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This document discusses how companies can make advanced analytics work for them. It outlines that fully exploiting data and analytics requires three capabilities: identifying and managing multiple data sources, building advanced analytics models, and transforming the organization so data and models yield better decisions. Two key features are having a clear strategy for how to use data/analytics to compete and deploying the right technology. The document provides three areas of action for organizational change: developing business-relevant analytics, embedding analytics into front-line tools, and developing capabilities to exploit big data. Managers need to understand how information can be used for key decisions and get creative about potential external/new data sources through targeted efforts.
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.
Making advanced analytics work for you
The document discusses how companies can make advanced analytics work for them by overcoming problems and fully exploiting data. It recommends that companies 1) identify multiple data sources and manage the data, 2) build advanced analytics models, and 3) transform their organization. It also stresses having a clear data strategy and the right technology. Managers are advised to develop business analytics, embed tools for front lines, and build big data capabilities.
Making advanced analytics work for you
The document discusses making advanced analytics work for companies. It provides guidance on choosing the right data, building models that predict and optimize business outcomes, and transforming a company's capabilities. It emphasizes starting with identifying a business opportunity and determining how analytics can improve performance. While big data can solve companies' problems, organizational change is needed to fully exploit analytics capabilities. Research shows companies using big data and analytics have 5-6% higher productivity and profitability than their peers.
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Big data and analytics have grown significantly over the past decade and companies are increasingly integrating them into their systems. While some view big data with skepticism, others have found success in using data to power decisions. To fully utilize big data, companies must identify and combine multiple data sources, build advanced analytics models, and transform their organizations to leverage the data models for better decisions. The types of data available have expanded vastly in recent years, so companies must carefully select data sources that can help solve business problems. Legacy systems may initially limit data usage, but integrating new technologies gradually can help companies develop predictive models and analytics capabilities to optimize outcomes.
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This document is an August 2019 marketing report from Burgundy Corporation about making advanced analytics work. It discusses how big data and analytics have become important for companies. While companies want to use data to drive decisions, most are unsure how to proceed and invest in analytics. The report explains that fully exploiting data requires the ability to manage multiple data sources, build advanced models, and transform the organization so data yields better decisions. It provides next steps and insights into developing a clear strategy, deploying the right technology, and making thoughtful organizational changes to use big data.
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Making advanced analytics work
Big data and analytics have become important business strategies. The document outlines two key insights for making analytics work: 1) Choose the right data sources and combine data to gain more granular business insights; and 2) Build predictive models that optimize business outcomes rather than just mining data. Managerial focus should be on developing the simplest models that improve performance.
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【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176555708】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176555708】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！
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
原版办【微信号:BYZS866】【兰加拉学院毕业证(Langara毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（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【微信号BYZS866】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【微信号BYZS866】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！
Experts live - Improving user adoption with AI
Bekijk de slides van onze sessie Enhancing Modern Workplace Efficiency op Experts Live 2024.
一比一原版(harvard毕业证书）哈佛大学毕业证如何办理
一模一样【微信：A575476】【(harvard毕业证书）哈佛大学毕业证成绩单Offer】【微信：A575476】（留信学历认证永久存档查询）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。
【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：A575476】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：A575476】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
→ 【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：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部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！
原版一比一弗林德斯大学毕业证(Flinders毕业证书)如何办理
原版制作【微信:41543339】【弗林德斯大学毕业证(Flinders毕业证书)】【微信:41543339】《成绩单、外壳、雅思、offer、真实留信官方学历认证（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！
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
原版一模一样【微信：741003700 】【(uts毕业证书)悉尼科技大学毕业证学历证书】【微信：741003700 】学位证，留信认证（真实可查，永久存档）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，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
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
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
UofT毕业证如何办理
原件一模一样【微信：95270640】【多伦多大学毕业证UofT学位证成绩单】【微信：95270640】（留信学历认证永久存档查询）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。
【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：95270640】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：95270640】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【微信：95270640】
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
→ 【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：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部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！
办理多伦多大学毕业证硕士毕业证成绩单UofT学位证【微信：95270640 】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理多伦多大学毕业证UofT学位证硕士毕业证成绩单【微信：95270640 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理多伦多大学毕业证硕士毕业证成绩单UofT学位证【微信：95270640 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理多伦多大学毕业证硕士毕业证成绩单UofT学位证【微信：95270640 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
Build applications with generative AI on Google Cloud
We will explore Vertex AI - Model Garden powered experiences, we are going to learn more about the integration of these generative AI APIs. We are going to see in action what the Gemini family of generative models are for developers to build and deploy AI-driven applications. Vertex AI includes a suite of foundation models, these are referred to as the PaLM and Gemini family of generative ai models, and they come in different versions. We are going to cover how to use via API to: - execute prompts in text and chat - cover multimodal use cases with image prompts. - finetune and distill to improve knowledge domains - run function calls with foundation models to optimize them for specific tasks. At the end of the session, developers will understand how to innovate with generative AI and develop apps using the generative ai industry trends.
一比一原版英属哥伦比亚大学毕业证(UBC毕业证书)学历如何办理
原版办【微信号:BYZS866】【英属哥伦比亚大学毕业证(UBC毕业证书)】【微信号:BYZS866】《成绩单、外壳、雅思、offer、真实留信官方学历认证（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【微信号BYZS866】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【微信号BYZS866】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(CU毕业证)卡尔顿大学毕业证如何办理
原件一模一样【微信：95270640】【卡尔顿大学毕业证CU学位证成绩单】【微信：95270640】（留信学历认证永久存档查询）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。
【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：95270640】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：95270640】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【微信：95270640】
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
→ 【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：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部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！
办理卡尔顿大学毕业证本科学位证成绩单CU学位证【微信：95270640 】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理卡尔顿大学毕业证CU学位证本科学位证成绩单【微信：95270640 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理卡尔顿大学毕业证本科学位证成绩单CU学位证【微信：95270640 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理卡尔顿大学毕业证本科学位证成绩单CU学位证【微信：95270640 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
Intelligence supported media monitoring in veterinary medicine
Media monitoring in veterinary medicien
End-to-end pipeline agility - Berlin Buzzwords 2024
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.
DSSML24_tspann_CodelessGenerativeAIPipelines
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
毕业原版【微信:176555708】【(GWU,GW毕业证书)乔治·华盛顿大学毕业证】【微信:176555708】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176555708】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176555708】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！
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
by
Timothy Spann
Principal Developer Advocate
https://budapestdata.hu/2024/en/
https://budapestml.hu/2024/en/
tim.spann@zilliz.com
https://www.linkedin.com/in/timothyspann/
https://x.com/paasdev
https://github.com/tspannhw
https://www.youtube.com/@flank-stack
milvus
vector database
gen ai
generative ai
deep learning
machine learning
apache nifi
apache pulsar
apache kafka
apache flink
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Monthly Management report for the Month of May 2024
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Making advanced analytics work for you
- 1. :- by Dominic Barton and David Court
- 2. OVERVIEW Big data and analytics have rocketed to the top of the corporate agenda. Companies like GOOGLE have been able to exploit the data. But most of the companies are unsure on how to proceed. They simply believe that their
- 3. Ways of fully exploiting data and analytics
- 4. Identify, combine, and manage multiple sources of data.
- 5. Build advanced analytics models for predicting and optimizing outcomes.
- 6. Possess the muscle to transform the organization so that the data and models actually yield better decisions.
- 8. Choose the Right Data
- 9. Get the necessary IT support.
- 10. Build Models That Predict and Optimize Business Outcomes
- 12. Develop business-relevant analytics that can be put to use
- 13. Develop capabilities to exploit big data
- 14. THANK YOU