1、AI and Analytics for IT LeadersTransforming the Enterprise with a Modern Data StackLAWRENCE MILLERAI and Analytics for IT LeadersTransforming the Enterprise with a Modern Data StackBy Lawrence MilleriiiDIRECTOR OF CONTENT DELIVERYWendy HernandezGRAPHIC DESIGNEROlivia ThomsonHEAD OF SMARTSTUDIOKatie

2、MohrPUBLISHERS ACKNOWLEDGEMENTSCopyright 2024 by Future US LLC Full 7th Floor 130 West 42nd Street New York,NY 10036All rights reserved.This book or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the publisher except for the use o

3、f brief quotations in a book review.Printed in the United States of AWITH SPECIAL CONTRIBUTIONS FROM ALTERYXMelissa BurroughsDIRECTOR,PRODUCT MARKETINGHeather FergusonSR.EDITORIAL MANAGERJohn MunyanGLOBAL BRAND AND CREATIVE CONSULTANTABOUT THE AUTHORLawrence Miller,CISSP,is an information security p

4、rofessional with more than 20 years of professional experience in various industries.He has written more than 200 books on a variety of information technology and security topics.ivENTERING THE JUNGLEChapter 1:Todays CIO Needs to Speak Both IT and MBA 7Turning Your Data into a Competitive Advantage

5、8Realizing a Shared Vision for AI and Analytics in Your Business 9Recognizing Competitive Differentiators in Your AI and Analytics Strategy 10Identifying GenAI and Analytics Use Cases for Your Business 12Bringing GenAI to Your Board 13Chapter 2:Employing AI to Your Advantage 15AI&Analytics:Breaking

6、Down the Barriers Between Your Data and Your Business Users 16Defining a Framework for Evaluating AI Use Cases 18Insights with Oversight:How Data Democratization and Governance Work Together To Boost Your Business 20Chapter 3:Optimizing Your Data Stack 27Defining the Modern Data Stack 27Planning for

7、 AI Success 29Realizing the Benefits of a Modern Data Stack 31Introducing the Alteryx AI Platform for Enterprise Analytics 32vCALLOUTS USED IN THIS BOOKKNOWLEDGE CHECKTests your knowledge of what youve read.WATCH OUT!Make sure you read this so you dont make a critical error!PAY ATTENTIONWe want to m

8、ake sure you see this!TIP A helpful piece of advice based on what youve read.DEFINITIONDefines a word,phrase,or concept.GPSWell help you navigate your knowledge to the right place.SCHOOL HOUSEIn this callout,youll gain insight into topics that may be outside the main subject but are still important.

9、FOOD FOR THOUGHTThis is a special place where you can learn a bit more about ancillary topics presented in the book.BRIGHT IDEAWhen we have a great thought,we express them through a series of grunts in the Bright Idea section.DEEP DIVETakes you into the deep,dark depths of a particular topic.EXECUTI

10、VE CORNERDiscusses items of strategic interest to business leaders.6INTRODUCTIONData is a powerful engine of business innovation.As organiza-tions increasingly rely on data-driven systems and applications to run nearly every aspect of the business,the quality and accessibility of their data take on

11、paramount importance.The rapid adoption of AI-based technologywhich is only as good as the data its trained onis further driving the need for high-quality,readily accessible data across the enterprise.IT leaders have a comprehensive under-standing of AI technologies,their benefits and challenges,the

12、 com-panys existing technology infrastructure,and most importantly,the strategic business vision that technology enables for the orga-nization.This puts them squarely in a unique position to lead their organizations AI initiatives.The Gorilla Guide To AI and Analytics for IT Leaders is your guide to

13、 pursuing the business imperative to turn your data into a com-petitive advantage.In this guide,well explore the evolving role of the modern CIO as a business leader,how to drive broad adoption of AI and analytics across the enterprise with strong governance and data democratization,and how a modern

14、 data stack helps your organization maximize the value of its data and achieve truly trans-formational AI and analytics outcomes.7IT leaders are increasingly responsible for business outcomes;a modern CIO needs to be thinking beyond traditional IT and have an impact on the overall business.Many are

15、concerned that their existing IT processes are slowing time-to-market,stifling innova-tion,and reducing agility,impeding new business opportunities and growth.IT leaders must understand business strategies and motiva-tions,and empower the business to be successful.Key focus areas for the modern CIO

16、include:Business growth.Technology decisions must align with the business goals and objectives to ensure IT is seen as a growth partner in the business,rather than just another cost center.Operational excellence.IT leaders contribute to a culture of excellence by maximizing the effective use of tech

17、nology,facilitating training to drive user adoption and productivity,efficiently managing licensing and procurement,and tracking technology impacts,among many other competing priorities.Customer experience.Delivering a superior customer experience to every customerincluding internal and external cus

18、tomersat every interaction is crucial CHAPTER 1 Todays CIO Needs to Speak Both IT and MBATODAYS CIO NEEDS TO SPEAK BOTH IT AND MBA8to business prosperity.IT leaders must recognize opportunities to differentiate the business through innovative uses of new and existing technology and data.Compliance.T

19、he regulatory landscape is a constantly evolving and increasingly complex environment.Data security and privacy concerns are driving new standards,laws,and regulations at state,federal,regional,and international levels.IT leaders recognize the business imperative to maintain compliance has never bee

20、n more challenging and urgent than it is now.Turning Your Data into a Competitive AdvantageArtificial intelligence(AI)(particularly generative AI,or genAI)and machine learning(ML)technologies are being rapidly adopted across industries and regions.But AI isnt just the latest“shiny new thing”or a pas

21、sing trendit is the critical technology shaping our future.However,AI is only as good as the data that feeds it.To differenti-ate your business from your competitors and gain a real advantage,you need to bring AI and analytics together to maximize the value of your data.Generative AI(genAI)is artifi

22、cial intelligence(AI)that can generate contentsuch as text,images,video,audio,or software codein response to a users query.It uses deep learning models and natural language processing(NLP)to learn the patterns and structure of input training data to create new content.TODAYS CIO NEEDS TO SPEAK BOTH

23、IT AND MBA9Realizing a Shared Vision for AI and Analytics in Your BusinessWith the seemingly sudden arrival and rapid adoption of tools such as ChatGPT,Gemini,Jasper,and others,AI(specifically,genAI),has become a distinct reality.GenAI learns from massive data sets and generates content such as text

24、,images,videos,music,and more.But genAI has far more potential than simply helping contact center agents triage customer inquiries or automating common IT requests(such as resetting a users password).When combined with analyt-ics,genAI streamlines and accelerates time-to-value across the data lifecy

25、cle from data cleansing to analysis and visualization,and drives better decision-making.Of course,AI is not without its challenges and risks.Unfortunately,many businesses dive headfirst into an AI initiative,often without understanding the potential pitfalls.The role of the modern CIO is to help the

26、 business safely navigate these uncharted waters,com-municating AI opportunities and proactively heading off challenges such as technical debt,quality of output,ethical issues,employee displacement concerns,and more.The modern CIO also plays an important role in dispelling myths and misinformation a

27、bout AI to help ensure the business understands the power and potential of AI and analytics together,as well as the limitations and risks.Developing appropriate governance helps ensure the business uses AI and analytics to unleash the power of data in a responsible manner,and does not run afoul of l

28、egal,regu-latory,and ethical requirements.As an organization matures in its use of AI and analytics,its AI strat-egy must evolve and scale to maintain a competitive advantage and explore new opportunities for its use.TODAYS CIO NEEDS TO SPEAK BOTH IT AND MBA10Recognizing Competitive Differentiators

29、in Your AI and Analytics StrategyThere are many opportunities for businesses to outperform their competitors with a well-defined AI and analytics strategy,including:Data quality.GenAI needs high-quality data to learn from and improve.Avoid the“garbage in,garbage out”(GIGO)problem by ensuring the utm

30、ost quality of your data.Proprietary data.Every organization has unique or proprietary data that helps inform everyday decision making.Leverage this data in your AI and analytics projects to ensure insights and results are tuned for your unique business.Data processes.AI can help you optimize and ac

31、celerate your data processes,including data cleansing and analysis to drive faster time-to-insight from your data.Predictive and prescriptive AI.While predictive and prescriptive analytics arent new,combining AI and analytics takes your data to another level by enabling you to not only anticipate ou

32、tcomes,but also receive recommendations for what to do based on those outcomes.Ethical and responsible AI policies.Ethics and the responsible use of AI are topics that are frequently covered in the news media,addressed by industry leaders,and debated in congressional hearings.Get ahead of these issu

33、es by developing robust and appropriate governance.TODAYS CIO NEEDS TO SPEAK BOTH IT AND MBA11 Expanded data and analytics access.Access to data analytics in many organizations is limited due to complex extract/transform/load(ETL)data management processes,siloed data in disparate platforms,and the n

34、eed for highly specialized development or data science skills.AI can help democratize your data by automating and accelerating these processes,leveraging data everywhere it lives,and delivering key business insights to all of your data consumers.Is Your Data Prepped and Ready for AI?Data preparation

35、 in most organiza-tions is time-intensive and repetitive,leaving precious little time for actual analysis.But you need AI-ready data to make the most of AI and get insights faster.A recent survey by IDC reveals the following consequences of poor data quality:Data decay:75%of decision makers say that

36、 data loses value within days.Data waste:33%often dont use the data they receive.Data neglect:70%say that data is being underutilized.TODAYS CIO NEEDS TO SPEAK BOTH IT AND MBA12Identifying GenAI and Analytics Use Cases for Your BusinessAs you develop your AI and analytics strategy and identify relev

37、ant use cases for your business,its important to understand several key genAI capabilities,including:Summarization creates concise summaries of long documents such as contracts,license agreements,technical manuals,and more,enabling users to get the relevant data they need more quickly.Code generatio

38、n helps developers by automating routine tasks,improving syntax,providing recommendations,generating tests,and modifying existing code,among others.Data generation creates new content,such as text,images,videos,and music.Leveraging these capabilities as building blocks,you can identify and inform th

39、e use cases that work best for your business.Some of the most common genAI use cases include:Text generation.Create copy in different voices,tones,and styles based on user input.Insight generation.Analyze different data sources to provide insights.Data set creation.Create synthetic data to train mod

40、els.Natural language interface.Use natural language processing(NLP)to interpret what is being asked,query data to find the result,and return findings that can be easily understood.TODAYS CIO NEEDS TO SPEAK BOTH IT AND MBA13 Workflow summary and documentation.Automate workflow documentation and impro

41、ve governance and auditability.Generate use cases.Identify,select,and build new analytics use cases.Bringing GenAI to Your BoardWhile many smaller companies and individuals have quickly embraced genAI technology,highly regulated industries and larger enterprises have been more hesitant to provide ge

42、nAI access to all employees.Corporate boards want efficiency gains and effective security,not greater risk exposure from genAI.According to a recent Alteryx survey,genAI is top of mind for most board members and 46%stated that genAI is currently their“main priority above everything else.”This respon

43、se was most common among board members who rated their understanding of genAI and the underlying technologies as expert(28%)or advanced(39%).And this is where the modern CIO can have perhaps the biggest impact on a companys future direction.As the corporate executive respon-sible for providing techn

44、ology leadership to the organization,the CIO has a unique perspective on AI and is in a position to ensure the board fully understands genAI technology,including opportunities,use cases,limitations,challenges,and more.Defining and quantifying success with AI for your board should focus on business o

45、bjectives and outcomes.Here again,the CIO is uniquely positioned to align AI solutions to business goals and objectives to achieve the desired outcomes.According to the Alteryx survey,for genAI to be considered successful by your board,operational consid-erations are key.The top four considerations

46、are listed in FIGURE 1.TODAYS CIO NEEDS TO SPEAK BOTH IT AND MBA14Clearly,genAI is a top priority for board members and is crucial to the future growth and success of your business.Now more than ever before,the modern CIO needs to speak a common language with board members and business leaders to en

47、sure the success of your genAI and analytics strategy.Now its time to focus on what you need to do to empower your business users,drive broad adoption of AI and analytics across the enterprise,and identify the AI and analytics use cases that will deliver transformational business outcomeswhich well

48、cover in Chapter 2.TOP FOUR OPERATIONAL CONSIDERATIONSCost efficiency40%Technical expertise31%User-friendliness25%Access to high-quality data24%FIGURE 1:Key operational considerations for genAI to be considered successful(Source:Alteryx,Board Member Pulse Survey,Oct,2023)15Generative AI(genAI)is top

49、 of mind for IT leaders as they seek to maximize the value of their data analytics while proactively managing the risks associated with genAI.Many leaders are nav-igating implementing AI responsibly with maximizing impact from the technology.What are companies realizing significant value from genAI

50、technologies doing differently?Research shows that they are using it more widely across the business than their competitors.These companies are more likely to provide open access to genAI tools for all employees,have greater confidence that their employ-ees have the right level of access to genAI,an

51、d find more opportuni-ties to derive value by making it available to more people throughout the organization.This is why IT leaders should be fostering a culture that trusts and empowers all employees to use genAI in their roles thereby maximizing the value of their genAI projects.In this chapter,yo

52、ull discover how to maximize the value of genAI and your data for competitive advantage.Well introduce a frame-work for evaluating AI use cases for your organization and explain how strong governance and data accessibility drives adoption across the enterprise.CHAPTER 2Employing AI to Your Advantage

53、EMPLOYING AI TO YOUR ADvANTAGE16AI&Analytics:Breaking Down the Barriers Between Your Data and Your Business UsersAs organizations increasingly embrace and adopt genAI,they are realizing ever greater value.Patterns and insights hidden within data can be discovered more quickly and repetitive tasks ca

54、n be automated,freeing up valuable resources to tackle more complex challenges.According to an Alteryx Pulse Survey,organizations are using genAI for content generation(46%),analytics insights sum-mary(43%),analytics insights generation(32%),code development(31%),and process documentation(27%).The t

55、op three benefits reported by companies in the survey of 300 data leaders across four countries are listed in FIGURE 2.TOP THREE BENEFITS OF GENAIIncreased market competitiveness52%Improved security49%Enhanced performance or functionality of their products45%FIGURE 2:Top three genAI benefits conside

56、red by companies surveyed(Source:Alteryx,Board Member Pulse Survey,October 2023)EMPLOYING AI TO YOUR ADvANTAGE17Bridging the Skills GapPutting analytics in the hands of domain experts sounds easier than it is in practice.It begins with the ability of business users to learn data sci-ence enough to s

57、peak the language and ask good questions.Here are a few strategies to help:Adopt a customer mindset.Be a good data science customer and collaborator by learning data science enough to speak the language and ask good questions.This helps business users get the most value from the expertise of the dat

58、a team.Close the gap in communication.Good dialog between data teams and business teams is one where people dont use jargon.If youre talking with a data person who throws out words like cross-validation or overfit,and you dont know what that means,you need to stop them and say,“Hey,Im not a data sci

59、entist.What does that mean?”Host upskilling workshops.There are proven benefits to upskilling efforts,including improved innovation,productivity,business growth,and employee retention.Consider proposing analytics days where domain experts can learn how to become better users of data tools and level

60、up their analytics skills.Organizations cannot rely on data scientists alone to generate business insights from the massive amount of data being created every day.Looking at it another way,it can be easier to teach an accountant the basics of data analytics than it is for a data scientist to learn t

61、he complexities of finance and accounting.EMPLOYING AI TO YOUR ADvANTAGE18Defining a Framework for Evaluating AI Use CasesDespite excitement over the potential of genAI,many companies are at a crossroads;theyre eager to harness the power of genAI,but find themselves facing a complex maze of implemen

62、tation challenges:Where do we start?Which use cases fit our business and will make the most impact?How do we know which to test first?In fact,identifying appropriate business use cases is the biggest hurdle to AI adoption.IT leaders are in a unique position to help their organizations maximize the v

63、alue of their data by responsibly empowering their users with genAI.Using genAI to score a quick win can help an organization build momentum for further genAI use cases that truly transform the business and maximize value.A simple framework for identifying AI use cases follows:Mitigate risk.Risk is

64、an important consideration when exploring potential use cases.Consider using data thats already public or would have minimal downside Businesses should instead focus on providing learning oppor-tunities and technology solutions for their existing workforce.Empowering knowledge workers with digital s

65、kills can deliver business value almost immediately while employees gain new skill sets that improve engagement,productivity,and retention.EMPLOYING AI TO YOUR ADvANTAGE19if exposed(for example,sales,marketing,customer support,and so on).Use a controlled environment that restricts access to data,con

66、tent,and interactions to allow experimentation with more sensitive data while minimizing the risk of exposure.For especially sensitive data sets,use genAI to create synthetic data.Once you show the synthetic data use case works,you can explore using real data.Automate repetitive processes.Look at an

67、y existing workflows and processes that are manual,repetitive,and labor-intensive.Due to their manual and mundane nature,these processes are often error-prone.Leveraging genAI can not only improve the efficiency of these processes but also free your employees to work on more strategic,value-added in

68、itiatives.Ensure human supervision.Using genAI with close human supervision is crucial,particularly in the early stages of identifying and testing various use cases.In addition to relying on your own workforce,working with trusted vendors can add another layer of security.In a recent Alteryx Pulse S

69、urvey,71%of respondents agreed that the risks associated with genAI can be effectively managed by using the technology within existing approved and trusted vendors.According to recent research,some of the most common genAI use cases for IT and data lead-ers include:Data analysis(43%)Cybersecurity(37

70、%)Customer support(34%)Code generation(32%)Financial forecasting(32%)Text generation(32%)EMPLOYING AI TO YOUR ADvANTAGE20Insights with Oversight:How Data Democratization and Governance Work Together To Boost Your BusinessIn companies lacking data governance,clarity and direction in ana-lytic process

71、es may be absent.Data analysts dont know which data is good and which is bad,and theyre constantly fighting fires across analytic processes.Good governance requires a solid strategy acces-sible to everyone who needs it.Your governance strategy should become second nature to everyone involved;it shou

72、ld be integrated into the very fabric of how you do business.Done right,governance is an enabler,not a blocker,for business success.IDENTIFYING STRATEGIES TO MAKE DATA ACCESSIBLEA modern data analytics stack is only as good as the ability of your employees to use it.IT leaders can give people across

73、 their organiza-tions access to data and analytics insights,while maintaining critical governance and visibility.A modern data analytics stack empowers different personas to leverage powerful cloud-based and AI tech-nologies.The following best practices will help you design a data analytics stack th

74、at will deliver value for your organization:Start simple.One of the benefits of a modern analytics stack is that its flexible and modular.You should be able to iterate and adjust as your business evolves.Get the basic pieces in placeincluding data warehouse/storage,visualization,analytics,and govern

75、ance elements.Choose technologies that support multiple deployment scenarios.Many organizations need to manage data pipelines across environments,including EMPLOYING AI TO YOUR ADvANTAGE21on-premises,hybrid cloud,multi-cloud,private cloud,and public cloud.When choosing your analytics platform,choose

76、 a platform thats compatible with your current ecosystem and flexible enough for your future one.Think about where you need to execute your analytics workflowsideally right where the data lives,to minimize costs and data movement.Accommodate different preferences for working with data.Applications t

77、hat offer low-code or no-code functionality are quickly becoming the norm for companies that recognize the value of collaboration and data democratization.Low-code and no-code functionality make it possible for workers with domain knowledge to contribute to analytics without having the training of a

78、 data scientist or data engineer.However,code-first and low/no-code solutions are not mutually exclusive.With the right tools,you dont need to limit more complex data tasks to highly technical employees.Make it realistic for the organization to use your technology investments.Business outcomes dont

79、just come from traditional tech roles.They come from all workers.And many data tools werent built for all workers;they were designed for specific roles.You cant expect your line-of-business analysts to know how to get to every data store,especially if they dont have the right tools for advanced anal

80、ysis and dont have sufficient access the the right data.This has left organizations with modern data infrastructure,like a cloud-based data warehouse or data lake,that isnt used to its full potential because its inaccessible to employees who lack technical skills.A modern data analytics stack provid

81、es a simple,accessible interface so that your data can be accessed and consumed by business users throughout the organization.EMPLOYING AI TO YOUR ADvANTAGE22Heres how you can have the visibility,control,and oversight you need while empowering more people with access to the data and analytics tools

82、they need to accelerate the business with insights from analytics:Establish a modern,flexible AI and analytics governance framework.Democratizing analytics doesnt necessarily mean chaos.Often,companies already have compliance policies and procedures in place that govern who and how data is used,as w

83、ell as change management procedures.Extending and updating these policies and procedures to cover the use of genAI throughout your company may be all that is needed.A modern,flexible governance framework has the following characteristics:Defense in depth.Governance is a multi-layered approach.It doe

84、s not rely on only one control point or tool.Instead,preventative and detective controls are leveraged throughout the entire analytic lifecycle.Segregation of duties.A key control principle is that no user can review,approve,and promote their own workflows to production.A robust review process and a

85、utomated migration between environments ensure the segregation of duties at all times.Good governance by design.Bring governance best practices to every aspect of workflow management using a flexible and customizable approach that leverages automated risk checks to allow you to identify,manage,and m

86、itigate risks.Fit for purpose.Not every workflow carries the same risk.Rather than adopting a“one-size-fits-all”approach,implement a streamlined process for low-risk workflows that facilitates innovation and rapid prototyping.EMPLOYING AI TO YOUR ADvANTAGE23 Assess each of your workflows risk levels

87、.What constitutes a low-versus high-risk workflow will depend on your organization.FIGURE 3 illustrates an example of a simple risk assessment questionnaire that assumes two risk tiers(high/low).To assess a workflows risk level,consider the following questions:GUIDING QUESTIONSWhat decisions are tak

88、en based on the information provided?Is there a material financial impact?Is there a risk to reputation?Is confidential data at risk?LOWER RISKHIGHER RISK Workflow performs simple,historical calculations Output will influence decisions with material impact Errors may impact earnings guidance to fina

89、ncial markets Workflow writes data to core enterprise systems Data output is shared outside of your team Confidential management reporting Decisions are not made based on a single input or report Non-confidential management reporting Non-financial public materialsFIGURE 3:An example of a risk assess

90、ment questionnaireEMPLOYING AI TO YOUR ADvANTAGE24 Will an error in this workflow result in a material financial impact or substantial reputation risk?Are we working with confidential or sensitive data(such as patient records or financial information)?In the face of unexpected staff turnover,can we

91、easily ensure that the workflow can be executed?Can we expedite new team members to step in and familiarize themselves with workflows and underlying logic?Do our policies and standards ensure data is correct,updated,and fit for purpose?Assemble your tactical toolkit.Your specific list of tactics can

92、 include things that are always required,tasks that are recommended,and then items particular to high-risk or low-risk workflows.While details will vary across industries,sectors,and use cases,some common guiding principles for good governance across these risk levels include:Lower-risk workflows:El

93、ements of good governance for lower-risk workflows are detailed documentation,independent reviews,and a formal sign-off/approval process.Specifically,it is helpful to document the calculation logic(either in the workflow or in an independent document),conduct an independent review process(within the

94、 team or by an outsider),track manager sign-offs,and maintain a change log with evidence of review.Higher-risk workflows:For higher-risk workflows it is valuable to maintain separate development and production environments with a formal process to promote to production,a formal review process for ex

95、isting workflows(with,depending on risk,either continuous monitoring or a routine cadence EMPLOYING AI TO YOUR ADvANTAGE25like annual re-validation),and control points with automated pass/fail triggers that stop execution if an error occurs.Prioritize administrative ease of use.Adopting a data solut

96、ion that enables self-service can appear to be a governance nightmare.How can you trust users throughout your company with the keys to the data?Administrative ease of use.Look for tools that dont just make it easy on the end user.They should make it easy on the administrator in charge of adding lice

97、nses,monitoring data usage,giving permissions,and ensuring things are running correctly.Prioritize governance capabilities that make responsibilities like auditing,provisioning,and risk mitigation easier:visibility:Is it easy to see what users are doing?Can you quickly view what jobs are running and

98、 which ones are scheduled?Scalability:Can you build pre-approved apps that allow users to ask their own questions,without touching the underlying data or workflows?Is role-based access control built into the data solution,so different users have the appropriate permissions?Data lineage:Can you track

99、 what happened to the data at each stage and get a simple summary of workflows?Or are you digging through messy SQL and local spreadsheets to understand whats happening?Your preferred UI:Your business users might be doing their data tasks in a more business-friendly,no-code platformbut that doesnt m

100、ean you have to be on their platform.If you spend your time in a cloud data warehouse,for example,can you monitor activity from other data tools from within that warehouse?EMPLOYING AI TO YOUR ADvANTAGE26If youre following governance best practices and vetted governance checklists,your analytic proc

101、esses will be robust and successful,which will lead to additional high-value work.Far from a chore,good governance is a win-win.But to implement a strong approach to governance,youll need a solid strategy.Once you have your gov-ernance best practices in place,your analytic processesand your teamwill

102、 be unstoppable.Turn the page to learn how a modern data stack helps your business maximize the value of data for competitive advantage.27We often hear about organizations undergoing“data modern-ization”to become more data-driven.Essentially,this means that these organizations have recognized that l

103、egacy data tools arent very good at solving modern data problems.Theyre moving data out of legacy databases and,at the same time,replacing legacy systems with an updated solution:a modern data stack.So,what exactly is a modern data stack and how does it improve analytics,surface actionable insights,

104、improve decision-making,and deliver positive outcomes?In this chapter,we define the mod-ern data stack,help you plan for a successful transformation of your data stack leveraging AI,explain the benefits of a modern data stack,and explore the Alteryx AI Platform for Enterprise Analytics.Defining the

105、Modern Data StackThe traditional(or legacy)data stack is typically built on SQL-based on-premises databases and data warehouses.In contrast,a modern data stack is a cloud-based unified platform that integrates various tools and technologies to ingest,organize,store,transform,analyze,and visualize da

106、ta.CHAPTER 3Optimizing Your Data StackOPTIMIzING YOUR DATA STACK28The journey from legacy to modern data stack doesnt have to be a“rip-and-replace”upgrade.Instead,many organizations will opt for an incremental approach using a transitional data stack(transition-ing from a legacy data stack to a mode

107、rn data stack)or a hybrid data stack(combining modern and legacy technologies).Here are some tips to help you plan your organizations journey to a modern data stack:Start by choosing a data warehouse that strikes the right balance between enabling self-service,ensuring strong governance,and empoweri

108、ng people with access at the right time.Choose intuitive,accessible analytics tools that are easy to learn and dont require special skills,all while leveraging your data warehouse to maximize the value of your technology investments with a seamless,end-to-end analytics process.Consider solutions tha

109、t integrate with any legacy systems you have while offering flexible options for where you store,process,and analyze data to ensure youre delivering a consistent experience as your stack evolves and your data moves between on-premises and cloud environments.Avoid adopting purpose-built tools,lest yo

110、u end up with many overlapping point solutions.Invest in upskilling and data literacy programs that enable employees to seek and question through data,ultimately changing how they operate and make decisions.OPTIMIzING YOUR DATA STACK29The crucial components and functions of a modern data stack inclu

111、de:Loading:Technologies in this category are respon-sible for moving data from one place to another.Warehousing:These are the technologies that allow organizations to store all their data in one place.Cloud-based data warehouses,lakehouses,or data lakes are the basis of modern data stacks.Transformi

112、ng:This stage turns“raw”data into“refined”datain other words,it makes data usable for analytics.Most organizations will use a“data preparation platform”for this stage.Analytics:At this point,organizations begin to derive meaningful insights from their data by fun-neling it into machine learning mode

113、ls and business intelligence tools,serving up to stakeholders as reports or visualizations,or using it as the basis of data applications.Planning for AI SuccessAs organizations transition from legacy data platforms and tools to modern data platforms,IT leaders aim to harness the full potential of th

114、eir data,leveraging the latest innovations,including AI.OPTIMIzING YOUR DATA STACK30Some key questions to consider include:Who owns the data?In many businesses,data isnt shared with everyone.Identify your data owners to help you understand the priorities of your various stakeholders.Who owns the bud

115、get?IT teams are generally responsible for data technology budgets.Ensure your budget has the flexibility to adapt rapidly to new opportunities and innovations.How are your data teams structured?In many organizations,data teams operate as distinct and separate teams.In others,theyre part of an overa

116、ll data leadership or IT leadership team.Organizations need their data to be AI-ready to move beyond using widely available large language models(LLMs)and fully harness the power of proprietary data.AI-ready data is high-quality,accu-rate,complete,and consistent.It must be in a format thats easily i

117、ngested by AI systems,regardless of whether the data is structured or unstructured.AI-ready data also has thorough documentation,including context,definitions,data lineage,and previous transfor-mations,ensuring transparency and understanding.A successful approach to data prep for AI-ready data inclu

118、des these functions:Data exploration:Discover what surprises the dataset holds.Data cleansing:Eliminate the dupes,errors,and irrelevancies that muddy the waters.Data blending:Join multiple datasets and reveal new truths.Data profiling:Spot poor-quality data before it poisons your results.OPTIMIzING

119、YOUR DATA STACK31 ETL(Extract-Transform-Load):Aggregate data from diverse sources.Data wrangling:Make data digestible for your analytical models.Realizing the Benefits of a Modern Data StackThe modern data stack delivers many business and technical bene-fits,including:Easy to use.A data stack is onl

120、y as good as your ability to use it.A modern data stack empowers your users to maximize the value of your data.Unified platform.A unified platform allows users to access,transform,analyze,and visualize data in one integrated experience.Advanced capabilities.The modern data platform includes the late

121、st innovations in Generative AI(GenAI),automated machine learning(AutoML),feature engineering,deep feature synthesis,and more.Scalable for the enterprise.The modern data platform supports flexible and incremental scalability to support the dynamic requirements of your business and users.Active commu

122、nity.Internal user groups are part of a larger community that helps an organization maximize the value of its data by engaging all data users to increase knowledge,share best practices,improve skills,and collaborate with other users.The ease of use in a modern data stack helps foster user communitie

123、s that add value to the organization.OPTIMIzING YOUR DATA STACK32Introducing the Alteryx AI Platform for Enterprise AnalyticsAlteryxs AI Platform for Enterprise Analytics enables customers to innovate,automate,and drive important business outcomes,includ-ing improving revenue performance,managing co

124、sts,and mitigating risks across their organizations(see FIGURE 4).Key platform capabilities include:GenAI and Conversational AI.Find insights faster with trusted analytics using GenAI and Conversational AI.ETL/ELT.Extract,transform,and load data to a variety of targets.Data prep,enrichment,and data

125、quality.Clean and prepare data for reliable analysis.FIGURE 4:The Alteryx AI Platform for Enterprise AnalyticsIntroducing the Alteryx AI Platform for Enterprise AnalyticsOPTIMIzING YOUR DATA STACK33 Analysis,geospatial,and AutoML.Leverage the power of automation and utilize more advanced techniques

126、in your analysis.Reporting,analytics apps,data stories.Surface insights and anomalies with AI and leverage self-service insights through analytic apps.Customer Story:Fender Brings Customers on the Guitar Journey with Alteryx+AWS+TableauFender Musical Instruments Corporation(Fender)designs and create

127、s the iconic guitars played by Jimi Hendrix,Nancy Wilson,Kurt Cobain,and H.E.R.In addition to the legends,Fender is on a mission to support music enthusiasts at any stage of their musical journey.As Fender guides beginners on their guitar journey,it uses data analytics to enhance the customer journe

128、y.Meghan Gohil,Automation and Data Visual Manager at Fender leads a team of data analysts who support cross-functional departments like marketing and finance in making intelligent decisions.By combining Alteryx with AWS,Tableau,and various data sources,Gohils team drives business impact on everythin

129、g from marketing campaigns to supply chain optimization to subscription revenue.UNDERSTANDING TODAYS GUITARISTS:AN OPTIMIZED DATA STACK ENABLES RICHER CUSTOMER INSIGHTSTodays musicians are a diverse,rapidly changing demographic(Fenders research found that 50%of the guitar-buying market OPTIMIzING YO

130、UR DATA STACK34is made up of beginner female guitarists).To understand its customers on a deeper level,Fender implemented an analytics process that gives the company a rich view of its market.Fenders team primarily uses Amazon Redshift for storage and computation and needed a way to optimize reporti

131、ng and visualization with Tableau.Before Alteryx,the team would output Redshift data directly to Tableau,and reports took a long time to generate.With millions of records and unaggregated data,the process was slow.Once the team adopted Alteryx,runtimes were significantly faster.A typical query that

132、might have taken three minutes now ran in seconds.One Tableau report took almost a minute and a half to load when done straight from Redshift.PREDICTING DEMAND WITH A MACHINE LEARNING MODELWhen Fender creates a new guitar,the team needs to forecast how many guitars to manufacture.Its an important ca

133、ll to make:Too many guitars can mean excess inventory.Its costly to store guitars,in part due to the climate control required to protect the delicate instruments.But if they make too few guitars,they miss out on potential revenue when demand peaks.To predict demand,the data team uses the Alteryx Des

134、igner Intelligence Suite to create a machine-learning model.They used social media data from platforms like YouTube and Spotify to gain deeper insights into each artists popularity.The model also includes factors like how long the artist has been in the market and the price point of the guitar.The p

135、redictions augment the decision-making with an intelligent data-driven approach.OPTIMIzING YOUR DATA STACK35ANALYZING CUSTOMER LIFETIME VALUE:WHEN EARNING A LIFETIME CUSTOMER MEANS CREATING A LIFELONG GUITAR PLAYERThe customer journey for any product has some friction.But when your customer journey

136、is the guitar journey,its even more challenging.The guitar is difficult to master,and beginners will often abandon the instrument in the first 90 days,even before they get good enough to buy more lessons and equipment.Fenders goal is to encourage guitar adoption,so players become valuable lifelong c

137、ustomers.Fender Play,Fenders online sub-scription-based platform for guitar,bass,and ukulele,utilizes strategically curated video lessons,which is one way Fender provides a path to playing.Fender created a workflow in Alteryx Designer that aggregates millions of records to find out which videos driv

138、e viewer engage-ment and lead to conversion.From there,the team can slice and dice the data in different ways to explore,investigate,and ask questions.How many videos do people watch before they subscribe?What types of videos hook people,and which ones drive them away?BENEFITS OF USING ALTERYX Faste

139、r workflow times.Alteryx drastically improved runtimes by optimizing the AWS+Tableau data stack.versatile use cases.Fender uses Designer for everything from automating Tableau reports to building a predictive model.Deeper-level analysis.Because Alteryx saves time building workflows,the team can get

140、deeper into the questions they want to answer and make a tangible business impact.OPTIMIzING YOUR DATA STACK36DRIVING ADOPTION AND ACTIONABLE INSIGHTSThroughout this Gorilla Guide,youve learned about the symbiotic relationship between data quality and successful AI and analytics outcomes for busines

141、s.From the top down,IT leaders are driving AI adoption in their organizations and empowering business users across the enterprise with analytics that deliver actionable insights and support better decisions with a modern data stack.Learn more about the modern data platform and discover the power of

142、bringing AI and analytics together to drive competitive advantage for your business at .37ABOUT ALTERYXAlteryx powers actionable insights with the AI Platform for Enterprise Analytics.With Alteryx,organizations can drive smarter,faster decisions with a secure platform deployable in on-prem,hybrid,an

143、d cloud environments.More than 8,000 customers globally rely on Alteryx to automate analytics to improve revenue performance,manage costs,and mitigate risks across their organizations.38ABOUT ACTUALTECH MEDIAActualTech Media,a Future B2B company,is a B2B tech marketing company that connects enterpri

144、se IT vendors with IT buyers through innovative lead generation programs and compelling custom content services.ActualTech Medias team speaks to the enterprise IT audience because weve been the enterprise IT audience.Our leadership team is stacked with former CIOs,IT managers,architects,subject matter experts and marketing professionals that help our clients spend less time explaining what their technology does and more time creating strategies that drive results.If youre an IT marketer and youd like your own custom Gorilla Guide title for your company,please visit .