1、1 TOP 10 BI&DATA TRENDS 2023Top 10 BI&Data Trends2023Calibrate for Crisis2 TOP 10 BI&DATA TRENDS 2023Power and data are shifting.Both are becoming fragmented.At this moment in history,were in a perfect storm.Geopolitical,social,and economic concerns are churning.Were seeing a rise in conflict and is

2、olationist tendencies;instead of a move toward cooperation,local regulations are amping up.In the economy,confidence is low,recession fears are high,and rising interest rates plus inflation are impacting borrowing.What do these factors have in common?More than a few scholars are claiming that were i

3、n the midst of a shift toward de-globalization.As it plays out,well see new fractures in old structures and the emergence of a state of multipolarity,or the distribution of power among multiple entities.And while the jostling will occur at the international level,well feel the impacts locally,in bot

4、h our businesses and personal lives.Among other repercussions,well be challenged with energy shortages,currency fluctuations,broken supply chains,and struggling markets.Multipolarity will also have a significant impact on informationtechnology.(See sidebar.)As data and analytics professionals,we nee

5、d to adjust to more fragmentation,with its disparate data centers,disrupted supply chains,nonstop innovation,and hampered access to skilled labor.And in a world where crisis has become a constant,calibrating for it becomes a core competency so we can react in the moment and anticipate whats coming n

6、ext.According to Gartner,by 2025,more than 50%of enterprise-critical data will be created and processed outside the data center or cloud.Gartner1Data has left the buildingMultipolarityDistributed DataSkills shortages exacerbatedVC funding dries outRegulations get more complicatedPossible splinternet

7、And hyperconnectivity,distributed ledgers,and Web3 may push fragmentation further.Multi-cloud impacts architecture2 TOP 10 BI&DATA TRENDS 20233 TOP 10 BI&DATA TRENDS 2023Its time to calibratefor crisis.And that requirestwo key competencies.During the pandemic,organizations acquired new technology si

8、mply to keep the lights on.In that sudden modernization,systems and processes became a chaotic tangle.Now its time to play catch-up in areas like governance,responsiveness,and cloud costs.In these challenging times,nearly 7 out of 10 global tech leaders are concerned about the growing technology inv

9、estment required to remain competitive.But few,if any,are looking to reduce their data efforts.Instead,surveys indicate that data integration,analytics,automation,API management,and AI are all top technologies CXOs rely on for crisis management.And nows the time to use them.In the coming year and be

10、yond,we believe it will be important to focus on two areas in particular:Calibrate the decisionHone your decision accuracy at speed and scale to better react to,adapt to,and even anticipateunexpected events.Calibrate the integrationWork to achieve connected governance the ability to access,combine,a

11、nd oversee distributed data sets to handle a fragmented world.What are the top 10 BI and data trends that will help you lead in an uncertain world?Find them in the pages ahead.*4 TOP 10 BI&DATA TRENDS 2023Calibrate the decisionSupply chain disruption meets real-time dataMarket consolidation opens ne

12、w opportunitiesWhats old is new again in the cloud“X-fabric”holds connected governance togetherAI moves deeper into the pipelineThe rise of derivative and synthetic dataDecision velocity at scaleOptimizing across low-code and high-codeThe human/machine arms raceData stories that compel actionCalibra

13、te the integrationTop 10 BI&Data Trends 20234 TOP 10 BI&DATA TRENDS 2023QLIK.COM5 TOP 10 BI&DATA TRENDS 2023Calibrate the decision1Supply chain disruption meets real-time dataAnyone who has attempted to buy a new car(or computer,or construction materials)in the last few years knows how se

14、riously supply chains have been compromised.Disruptions can happen anywhere in the world,and they require an immediate response.That means acting on contingency plans and even,if possible,“pre-acting”in other words,using forecasts and scenarios to pivot before things begin to break down.The infrastr

15、ucture to handle real-time data has been in place for some time,but the critical use cases and ultimate potential havent been fully explored.Now they should be.Were faced with managing inventory when raw materials are scarce and shipping is disrupted;needing to pinpoint supply chain bottlenecks to b

16、ackfill and work more effectively with partners;and having to shift resources to tackle new opportunities or address humanitarian needs when conflicts arise.And the pace of these issues is only going to accelerate.The pandemic and conflict in Ukraine have created significant components shortages.Thi

17、s backdrop has become the trigger for organizations to update their data-delivery pipelines,from batch-oriented to near real-time data.And as more edge devices appear on the grid producing continuous,high-volume streams of data more opportunities to leverage real-time data will arise.By 2027,60%of s

18、pending on data capture and movement technology will be on streaming data pipelines,enabling a new generation of real-time simulation,optimization,and recommendation capabilities.”IDCThe ImpactAnalyst Prediction5 TOP 10 BI&DATA TRENDS 20236 TOP 10 BI&DATA TRENDS 2023Calibrate the decision2Decision v

19、elocity at scaleOnce you have real-time data in place,the next step is to tune your operational decisions to the same pace.Analyst PredictionFor example,during times of inflation,its unsustainable for a retailer to push all their cost increases to customers.Instead,they should improve efficiencies t

20、housands of them,occurring thousands of times a day.By 2026,85%of enterprises will combine human expertise with AI,ML,NLP,and pattern recognition to augment foresight across the organization,making workers 25%more productive and effective.”IDCAutomation will help.According to Gartner,95%of decisions

21、 based on data can be at least partially automated,and in a more challenging environment,automation will accelerate.But even though analytics,AI,and automation can make more and faster decisions than humans,make sure to place humans at the beginning and the end of decision-automation cycles for desi

22、gn and review.Decision velocity at scale is also about shortening the data-to-action pipeline for humans decreasing the time it takes for people to find data and increasing the frequency of acting on it.In addition to technology,data literacy is a key enabler for that.And finally,decision velocity l

23、eaves a big data trail,with patterns that can be analyzed.That will create an opening for decision-mining.New roles will emerge with a focus on decision innovation such as Chief Decision Officer,Decision Designer,and Decision Engineer.These roles should be tasked not only with automating routine dec

24、isions but also with addressing the biggest,thorniest problems you face.6 TOP 10 BI&DATA TRENDS 2023The Impact7 TOP 10 BI&DATA TRENDS 2023Calibrate the decision3Optimizing across low-code and high-codeIn recent years,weve seen the emergence of low-code tools for building applications,enabling non-te

25、chnical workers to compose their own apps.One prominent tool is GitHub Copilot(based on GPT-3),which translates plain English into code.GitHub estimates that Copilot generates roughly 30%of the application code created on the site.On the other hand,some organizations have progr ammers and app develo

26、pers who simply want prompts they can code in.This isparticularly the case in data engineering and data science,as those fields get reinvented for cloud.To cater to these needs,weve seen the emergence of high-code tools,which provide templates for coders who want maximum flexibility.These tools not

27、only drive the creation of apps,they also increase the consumption of data and insights.For example,application automation enables workers to create chains of events triggered by data.AutoML gives business analysts access to the most advanced algorithms.And data transformations within data-delivery

28、pipelines can be largely automated,too.These two camps will always exist,though many use cases will gradually evolve from high-code to low as repeatable workflows are identified and markets mature.Still,the choice shouldnt be between low-code and high-code.Instead,it should be code optimization,focu

29、sing on the highest productivity and best business outcomes given the available skill sets.By 2023,60%of net-new applications will be developed with no-code/low-code platforms,up from 30%today.”IDCAnalyst Prediction7 TOP 10 BI&DATA TRENDS 2023The ImpactAnalyst Prediction8 TOP 10 BI&DATA TRENDS 2023C

30、alibrate the decision4The human/machine arms raceIn the summer of 2022,a Google engineer claimed that one of the companys chatbots(named LaMBDA)had achieved consciousness,or a human level of self-awareness.Google stated that his claims were unfounded and the engineer was fired for violating company

31、security policies but this incident shows how far machines have come in a short time.Because natural language models have been trained on massive troves of data using deep-neural-network machine learning,theyve reached a paradigm shift.Perhaps the most widely publicized is GPT-3.Its so capable that

32、its spawned a number of services,from code optimization,to writing marketing copy,to mimicking the voices of authors like Kafka and Hemingway.There are now 5-6 global developments even bigger than GPT-3,models trained on even larger data sets.Where those will take us,we can only imagine.We may be ab

33、out to cross the Rubicon where machines can finally pass the Turing test.In the space of data and analytics,natural language capabilities will have huge implications for how we query information and how its interpreted and reported.Well find not only the data were looking for but also the data we ha

34、dnt thought to ask about.Analyst PredictionIn the next five to 10 years or sooner,based on the groundbreaking innovation in AI,TuringBots will be created by several tech vendors.”Forrester Research8 TOP 10 BI&DATA TRENDS 2023The Impact9 TOP 10 BI&DATA TRENDS 2023Calibrate the decision5Data stories t

35、hat compel actionFor decades,we in the dataindustry have shared a mantra:Provide the right information to the right user at the right time.Thats more important now than ever.But in a fragmented world,where data is distributed and time is scarce,its tougher to do.Fortunately,you dont have to get all

36、the data to all the people all the time.Having the right slices of small data at the right time is more useful.And not every insight has to be arrived at through user exploration.Many can be more prescriptive and recommendation-oriented,delivered straight from the data.Data storytelling has been tou

37、ted as the way to get data to make sense to users;stories can reach people emotionally and compel them to act when data alone does not.But data storytelling needs to be much more than adding charts to infographics or PowerPoints.It needs to be connected with action.To connect storytelling to action,

38、you need to add three steps:1.Predicting what will happen next and suggesting best actions with AutoML2.Using alerting,reporting,and automation to bring stories into workflows at the right time3.Embedding not just dashboards but micro-stories into the systems where people work.That will move data st

39、orytelling from insights you could act on to insights you do act on.Analyst PredictionBy 2025,data stories will be the most widespread way of consuming analytics,and 75%of stories will be automatically generated using augmented analytics techniques.”Gartner9 TOP 10 BI&DATA TRENDS 2023The Impact10 TO

40、P 10 BI&DATA TRENDS 2023Calibrate the integration6Market consolidation opens new opportunities.In an increasingly fragmented world,theres also a market trend in the opposite direction:convergence.Were seeing the consolidation of previously siloed systems,including data integration,management,analyti

41、cs/AI,visualization,data science,and automation.Combining these functions opens opportunities that werent possible before.It makes it easier for data producers and consumers to collaborate,starting with the product,outcomes,or decisions they have in mind and working backward to build agile data pipe

42、lines around their business goals.Common standards and APIs enable interoperability.And when a vendor operates across more segments,convergence is even easier.This isnt about going“all-in”on one data stack,which can lead to vendor lock-in or compromise compliance.Instead,choose platforms that can wo

43、rk with multiple stacks,and consolidate the data across them.The move toward consolidation on the supply side is met by the demand side.In challenging times,CFOs and CEOs get more involved in the business,and they want to see ROI articulated clearly.This will help drive pricing models away from per-

44、user toward the value generated.After all,you cant predetermine who in your organization should use what tool when you dont know where the next challenge will come from.Instead,facilitate general access to tools and platforms,in a governed way,and build from there.By 2023,the stand-alone data prepar

45、ation market will disappear,and data preparation capabilities will be embedded within modern data management,analytics,and data science tools.”Gartner10 TOP 10 BI&DATA TRENDS 2023The ImpactAnalyst Prediction11 TOP 10 BI&DATA TRENDS 2023Calibrate the integration7Whats old is new again in the cloudDur

46、ing the pandemic,organizations quickly modernized applications and moved data to the cloud.This has created a Wild West of startups(often dubbing themselves part of“the modern data stack”)fueled by venture capital,each going after one specialization.And while winners will certainly emerge,the vast m

47、ajority will disappear as industries mature and consolidate.And this trend will accelerate as VC funding goes from boom to bust.(In Q3 2022,VC funding declined 53%,an early signal of what may come.)In other words,expect a big wave of M&A as small vendors look for the exit.It happened in the on-prem

48、world,and itll happen again in the cloud.As these changes mature,many of the same issues from the on-prem world are rearing their heads.For example,after you adopt a cloud warehouse or lake,you need to tackle data movement,transformation,metadata catalogs,and so on.These needs are driving investment

49、 in a multitude of software segments around warehouses and lakes including semantic layers and data integration,movement,sources,and observability.From a cost perspective,its not sustainable for organizations to work with a wide array of niche vendors.Fortunately,many of the features will be recreat

50、ed in the larger integrated data and analytics platforms.As cloud markets mature,managers may abandon architectures reliant on too many startups that struggle.Instead,these startups may be used as a source for“acqui-hires.”To help alleviate the developer skills shortage,55%of organizations will use

51、cloud marketplaces and tech startup acquisitions as their most important approaches to software sourcing by 2024.”IDC11 TOP 10 BI&DATA TRENDS 2023The ImpactAnalyst Prediction12 TOP 10 BI&DATA TRENDS 2023Calibrate the integration8“X fabric”holds connected governance togetherThe discussion in recent y

52、ears has been about data fabric(as well as hubs and mesh),an important methodology that connects distributed data sets through semantic models.But for connected governance,we need more than that.In a world with millions of builders,we need other fabrics,or“X fabrics.”These include application fabric

53、,BI fabric,and algorithm fabric and right now,these methodologies are even less mature than data fabric.Being able to reuse data and analytic assets is critical,spanning models,scripts,and analytics content.And the need for reuse also underscores the importance of the catalog,as well as its evolving

54、 role.Common APIs will make it possible to have modularity and composability,and catalogs can provide the oversight that spans artifacts.For connected governance,you need X fabrics.You also need to certify artifacts based on how trustworthy they are for example through watermarking based on threshol

55、ds.Every organization today is looking for better ways to access their data and analytic artifacts.And in a distributed world,orchestration becomes even more important.By 2023,60%of G2000 enterprises will have a data control plane architecture to enable DataOps,propel ML-based data engineering,reduc

56、e data risks,and propel innovation among Gen D workers.”IDC12 TOP 10 BI&DATA TRENDS 2023The ImpactAnalyst Prediction13 TOP 10 BI&DATA TRENDS 2023Calibrate the integration9AI moves deeper into the pipelineAs we mentioned in Trend 6,analytics,automation,and AI are converging,increasingly overlapping w

57、ith each other.In the process,theyre cross-pollinating,generating new insights that werent possible before.Using AI in data management would shift the perennial 80/20 distribution(between preparing the data and analyzing it)by automating more of the rote tasks in data engineering.It could,for exampl

58、e,automate anomaly detection and reporting,take advantage of self-healing,use just-in-time deployment,and find risky attributes such as PII data.Algorithms would be able to“crawl”the data and surface insights outside your hypothesis.And finally,automated annotations and tagging would drive better en

59、gagement with less skilled integrators.But what about moving those components deeper into the data pipeline,before an application or dashboard has even been built?There are several ways this could benefit organizations.More AI in the data pipeline doesnt mean that humans wont be involved.After all,h

60、umans are exceptionally good at synthesizing complex problems with multiple component parts.But AI will automate some of the more manual data preparation tasks,so data engineers and scientists can focus on more impactful work.Through 2024,manual data integration tasks will be reduced by up to 50%thr

61、ough the adoption of data fabric design patterns that support augmented data integration.”Gartner 13 TOP 10 BI&DATA TRENDS 2023The ImpactAnalyst Prediction14 TOP 10 BI&DATA TRENDS 2023Calibrate the integration10The rise of derivative and synthetic dataData is a liquid asset;it can look different for

62、 different purposes.In other situations,useful data simply doesnt exist.The lack of available user data,for example,can be problematic for small businesses,who wont be able to train their AI models with vast data sets.Or an enterprise may want to run experiments and what-if analyses for cases simula

63、tions of financial crime and fraud,for example.In both of the scenarios above,synthetic data can be an option.Synthetic data is data that has not been generated from real operations.And today,its easier than ever to alter data for different use cases or transform it into formats for specific targets

64、.Data that has been transformed,processed,aggregated,correlated,or operated on is called“derivative”data.Derivative data has been especially useful for test data management creating,managing,and delivering test data to application teams.But now,with new privacy laws and integrity issues,its becoming

65、 essential to obfuscate data even further.Thanks to a number of factors including data re-use,testing,privacy laws,missing data,and the need for data to train AI models well see more derivative and synthetic data.By 2030,synthetic data will completely overshadow real data in AI models.”Gartner 14 TO

66、P 10 BI&DATA TRENDS 2023The ImpactAnalyst Prediction15 TOP 10 BI&DATA TRENDS 2023The way forward.What do these trends mean for you?In a fragmented world where crisis has become a constant,its important to innovate and be prepared.Start by thinking through how these trends apply to your organization.

67、Identify use cases where real-time data and decision velocity can address challengesLook for ways to converge siloed technologiesUse a fabric not just for your data but for other artifacts as wellApply AI earlier in the data pipelineLeverage the VC crunch to remediate urgent skills shortagesLook at

68、derivative and synthetic approaches as ways to maximizevalue in a distributed worldLeverage the right mix of code optimization for your business users and engineersSee how data storytelling can be more closely linked to actionUse innovations in natural language to bring data querying,insights,and ac

69、tions to more peopleData professionals of all kinds willplay a key role in calibrating through crisis.In a deglobalizing world,localized sourcing of those professionals will become increasingly important.Key to this is increasing the data literacy of your existing workforce,using both education and

70、technology.Its about more than just the technology.15 TOP 10 BI&DATA TRENDS 202316 TOP 10 BI&DATA TRENDS 2023To give you the power toanticipate,pivot,and navigate through crisis.Were here to helpGet ready for whats coming.See How Were DifferentGet in TouchPrefer a conversation?Our goalWhile multipol

71、arity is an unpredictable state,data and analytics can help reduce uncertainty.And fragmentation does hold promise;it could move the world to a longer-term vision of data democracy.In the meantime,addressing these trends will drive critical efficiencies in the here and now.And it could lay a foundat

72、ion for a massive cycle of innovation and prosperity,accelerating growth as we turn the corner.Qlik is designed to empower everyone in your organization,no matter their skill level,to combine data from a multitude of sources,explore it freely in an intuitive way,and make associative discoveries that

73、 other solutions wont uncover.With end-to-end data integration and analytics solutions,powerful boosts to data literacy from AI,and an independent open platform that enables you to embed analytics anywhere,Qlik helps you achieve Active Intelligence in your organization continuous intelligence where

74、technology and processes support the triggering of actions from accurate,up-to-date data.16 TOP 10 BI&DATA TRENDS 202317 TOP 10 BI&DATA TRENDS 2023Qliks vision is a data-literate world,where everyone can use data and analytics to improve decision-making and solve their most challenging problems.Qlik

75、 offers real-time data integration and analytics solutions,powered by Qlik Cloud,to close the gaps between data,insights and action.By transforming data into Active Intelligence,businesses can drive better decisions,improve revenue and profitability,and optimize customer relationships.Qlik serves mo

76、re than 38,000 active customers in over 100 countries.About Q 2023 QlikTech International AB.All rights reserved.All company and/or product names may be trade names,trademarks and/or registered trademarks of the respective owners with which they are associated.1 Goasduff,Laurence,“12 Data and Analyt

77、ics Trends to Keep on Your Radar,”Gartner,April 5,2022,https:/ Future Enterprise Resiliency and Spending Survey,IDC,April 2022.3“The Foundation of Data and Analytics is Cloud!,”Gartner BI Summit,2021 Gartner CIO Survey;and Qlik,QlikWorld,customer and former competitor interviews,BCG analysis.4 IDC F

78、utureScape:Worldwide Data and Content Technologies 2022 Predictions,https:/ to Become a Data-Driven Organization?Start with 5 Key D&A Initiatives,”Gartner,https:/ IDC FutureScape:Worldwide Artificial Intelligence and Automation 2022 Predictions,https:/ Coberly,Cohen,“Almost 30 percent of new GitHub

79、code is written with AI assistance,”TechSpot,October 28,2021,https:/ IDC FutureScape Worldwide Cloud 2022 Predictions,https:/ Grant,Nico,“Google Fires Engineer Who Claims Its A.I.Is Conscious,”New York Times,July 23,2022,https:/ Branch,Jr.,John E.,“Machine writing is becoming more human all too huma

80、n,in some cases,”Fast Company,September 19,2022,https:/ Response:You Should Be Running Toward AI with Eric Schmidt,”Masters of Scale with Reid Hoffman podcast,https:/ Lo Guidice,Diego,et.al.,“Prepare For AI That Learns To Code Your Enterprise Applications(Part 2),”Forrester Research,July 8,2021,http

81、s:/ Gartner:Data Storytelling:Analytics Beyond Data Visualizations and Slideshows,July 19,2021.14 Zaidi,Ehtisham,“Utilize Self-Service Data Preparation to Ease Rising Data Engineering Challenges,”Gartner Data&Analytics Summit 2022,slide 14.15 Teare,Gen,“Global VC Pullback is Dramatic in Q3 2022,”Cru

82、nchbase News,October 6,2022,https:/ IDC FutureScape:Top 10 Predictions for the Future of Innovation,November 12,2021,https:/ IDC FutureScape:Worldwide Data and Content Technologies 2022 Predictions,https:/ Gartner,Magic Quadrant for Data Integration Tools,August 17,2022,https:/ Linden,Alexander,“Is Synthetic Data the Future of AI?”Gartner,June 22,2022,https:/ TOP 10 BI&DATA TRENDS 2023