28:null 29:["$","title",null,{"children":"State of Dataviz | João Ricardo Mendes | Observable"}] 2e:Ta7a,#4 Estimar a probabilidade de transição de estados a partir das frequências de transição e criar uma estimativa de tempo médio de transição entre eles para o time de Operações #7 Projetar o valor econômico de um pacote a partir das probabilidades de transição e dos respectivos fluxos de caixa que cada estado representa #12 Criar uma forma visual de enxergar o acervo de pedidos que temos a operar e a maturidade respectiva de cada voucher #14 Descobrir se existem padrões comportamentais dentro de pacotes 'bem-sucedidos' (isto é, que fazem dinheiro) ou 'mal-sucedidos' (por exemplo: pacotes mal-sucedidos podem ter número médio de transições de estado maior/menor que pacotes bem-sucedidos) #19 Projetar o prazo médio de pagamento #15 Rebalancear o mix da prateleira de pacotes para favorecer fluxos de estados mais vantajosos financeiramente #11 Estudo dos estados mais propensos a iniciativas terceiras (cross sell, devolução em crédito, etc) #9 Criar uma north metric que resume a saúde dos pacotes do Hurb #3 Permitir estudos para cada linha de produto vendido, ou mesmo para cada pedido individual, do valor econômico realizado #5 Criar um método de estimação de probabilidades de transição de estados usando dados históricos #6 Estudar diferenças de frequência de transição entre pacotes de qualidades diferentes (ex: doméstico vs internacional, Orlando vs Punta Cana, São Paulo vs Rio de Janeiro, etc.) #2 Balancear a prateleira com pacotes com riscos complementares (hedge entre pacotes) #8 Demonstrar quantitativamente qual a necessidade de estoque futuro de quartos/hotéis/aéreo a partir da projeção de prazo médio de transição de estados #10 Criar uma intução sobre o que temos de estoque de hoteis/quartos que é atraente ao cliente (a partir da informação de quais hoteis/quartos são efetivamente operados) #16 Criar uma fonte da verdade confiável para projeções de breakage e cancelamento #1 Criar um histograma de tempo de transição de estados condicional a uma lista de pré-condições (por exemplo: responder a pergunta 'quanto tempo precisa para um pacote de Orlando vendido no Black Friday 2021 chegar ao estado "Resolvido", dado que ele passou pelo estado "Pagamento pendente" mas hoje está em "Aéreo emitido"?) #13 Avaliar se o sistema de Operações (que foi a origem desse data set) possui ou não todos os Estados que precisamos para entender o negócio de pacotes #17 Antecipar impacto que mudanças recentes em frequências de transição podem ter no atendimento #18 Projetar impacto financeiro de iniciativas que podem alterar as frequências de transição entre os estados 2f:Td0d,// order hard-coded based on responses to survey tools = d3.tsvParse( `category tool Developer Python Analytics Jupyter Analytics R Developer Visual Studio Analytics Excel Developer React Developer D3 Developer Github Analytics Google Sheets Analytics RStudio Analytics Tableau Developer Javascript Design Adobe Illustrator Developer Vue Collaboration Codepen Design Figma Developer Pandas Developer Git Analytics Altair Data Databases Developer Julia Analytics Matplotlib Developer SQL Collaboration Codesandbox Developer NPM Business Grafana Analytics Plotly Developer Vega Developer Atom Developer awk Developer S3 Developer Big Query Analytics Google Colab Developer Yarn Data Flourish Data Google Data Studio Developer Intellij Business Kaleidoscope.app Analytics Mathematica Developer Notepad++ Analytics Numpy Developer Pluto.jl Data Postgresql Business Power BI Analytics Seaborn Developer sed Data Stata Developer Sublime Text Developer Svelte Developer Typescript Developer SigmaComputing Communication Email Design Affinity Designer Developer Storybook Developer AMCharts Data Datawrapper Communication Confluence Communication Elasticsearch Business Dydra Business Oracle Analytics Collaboration Google Apps Collaboration JsFiddle Collaboration Google Drive Collaboration Google Slides Data Zepplin Analytics Airtable Developer API Tools Developer Nodejs Developer Webservers Developer Flask Developer .Net Developer C++ Developer Perl Developer MariaDB Developer PostgreSQL Developer Webstorm Developer Angular Developer grep Developer eslint Developer Express Developer Mongo Developer Sqlite Collaboration Draw.io Collaboration rawgraphs.io Developer Pentaho Developer MaMP Pro Developer Expresso Developer Azure Developer Shellscripts Developer Astrobuild Developer PHP Analytics MySQL Analytics Libreoffice Developer LaTeX Developer P5.js Developer Glamourous Toolkit Developer Prettier Data Plotly Analytics Amplitute Business Stripe Collaboration Salesforce Data VisiData Data GraphQL Data Drawbot Collaboration Chartio Data Domo Developer DatagripI Design Inkscape Developer Go Developer Sublime Text Communication Wordpress Developer HTML Developer XML Developer OpenMapTiles Developer MapBox GL Communication Davinci Resolve Data Athena Developer Lamda Collaboration Quokka Developer Nova Editor Developer Shiny Data Gephi Data Mathworks Developer Zsh Developer MDN Developer StackOverflow Data BigQuery Analytics SigmaComputing Data PyCharm Developer Anaconda Developer Anylogic Analytics Apache Echarts Developer Coffeescript Developer Dash Developer Dc.js Developer Domo Data Excel Other Filemaker Data Firebase Data GraphViz Data Hasura Data Mariadb Developer Meteor.js Developer Microsoft Bonsai Developer Ngrok Developer Node Repl Other Nova Data Openrefine Analytics Oracle Analytics Data Panda Developer Postgis Analytics PowerBI Analytics PowerQuery Communication Powerpoint Communication Prezi Data qgis Data qri.io Developer Repl.it Developer Rollup.js Developer s3 Collaboration Sharepoint Other Snagit Developer Spice Data Spyder Other Stackblitz Data Streamlit Developer Terminal Developer Tikz Developer Turf.js Communication Twitter Developer Unity Developer Vega-lite Developer Vim Data Visidata Data Wavefront Developer Webpack Developer Webstorm Communication Wordpress Developer XSL Data Zeppelin` )30:[] 2c:{"id":"0c4df5232c66bd74","slug":null,"title":"State of Dataviz","thumbnail":"ad81bbc0b290793cfec89555d086d9459755dcffe30dd49e778969e0006682a8","access_level":"public","create_time":"$D2022-11-01T17:04:38.609Z","update_time":"$D2022-11-01T17:06:06.371Z","view_time":null,"first_public_time":"$D2022-11-01T17:04:38.609Z","has_unpublished_edits":null,"fork":{"id":"dabff1a1753194ae","slug":"state-of-dataviz-2021","title":"State of Dataviz","owner":{"id":"f35c755083683fe5","login":"observablehq","name":"Observable"}},"stars":1,"starred":false,"owner":{"type":"team","id":"7632798b0a0057f3","login":"joaormendes","name":"João Ricardo Mendes","avatar_url":"https://avatars-next.observableusercontent.com/5a37070bf9e58604859ec9aa7033b0dcb40e61c4ff0aeaba33424ba04567b1fd","tier":"pro_2024"},"version":2340,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"fb55e01b401bd78d","login":"joaohurb","name":"João Ricardo Hurb Com","avatar_url":"https://avatars-next.observableusercontent.com/5a37070bf9e58604859ec9aa7033b0dcb40e61c4ff0aeaba33424ba04567b1fd","tier":null}],"members":[{"type":"individual","id":"fb55e01b401bd78d","login":"joaohurb","name":"João Ricardo Hurb Com","avatar_url":"https://avatars-next.observableusercontent.com/5a37070bf9e58604859ec9aa7033b0dcb40e61c4ff0aeaba33424ba04567b1fd","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"State of Dataviz","cells":[{"id":0,"value":"# State of Dataviz\n## 2021 Observations: Data through the lens of the Observable Community\n\n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1655,"value":"One of Observable’s motivating principles is to listen to and learn from its passionate and fast-growing community. \n\nHundreds of our community members generously participated in two research surveys about data analysis and visualization over the past year. Here’s what we learned.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2222,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":114,"value":"## Data is exploding, for everyone","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":90,"value":"With the explosive growth in online technologies, services and information, [data is overwhelming](https://seedscientific.com/how-much-data-is-created-every-day/) for all of us. Making sense of it is the biggest issue facing our connected world. For businesses, there is an urgent need for cross-functional teams to gain data-driven insights quickly to inform business decisions. \n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2218,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":111,"value":"## The data visualization community is growing","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":127,"value":"Observable’s survey data shows accelerated interest and growth in data visualization. This is confirmed by other industry observers: [Fortune Business Insights in 2020](https://www.fortunebusinessinsights.com/data-visualization-market-103259) estimated a market size of $8.85B as of 2019 and projected growth (CAGR) of 10.2% through 2027.\n\nThis growth in business investment and community size makes it clear that businesses are prioritizing tool investments for their teams to work with data, and gain data-driven insights.\n\nOur surveys show that working with data is no longer something that primarily specialists do; *working with data is increasingly becoming a critical skill* for many jobs. More people are investing in their own data-centric skills to meet the rising business needs, and to excel in their chosen professions.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2215,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2214,"value":"## Data Practitioners: data specialists and their collaborators","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2213,"value":"The people investing in their data skills are in different job functions. They analyze data, share insights and communicate with each other:\n- Data scientists\n- Data engineers\n- Data architects\n- Business and financial analysts\n- Data visualization (dataviz) creators\n- Business Intelligence / Operational dashboard developers\n- Those who collaborate with the above, such as product managers, team leads, and decision makers\n\nObservable uses the term *data practitioners* as an inclusive identity covering all of the people who work together on data.\n\n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1495,"value":"#### Which role best describes you?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":941,"value":"Rolepie = pieChart(roles, \"Role\", \"count\", \"dataRole\", \"Responses for data-centered roles\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1972,"value":"Note that for the “hobbyist” category, deeper inspection showed that these people were in fact doing data-work, including data exploration, data analysis, data visualizations and dashboard creation, etc. They self-identified as hobbyists because they were doing this work in a personal capacity and not as part of their official job. This further strengthens the hypothesis on the broadening group of data practitioners honing their data-related skills.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2212,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2211,"value":"## More practitioners are entering the field to match industry demand","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1857,"value":"We're seeing that *more and diverse* practitioners are entering the field and beginning to sharpen their skills with languages and libraries for more complex data visualizations. This growth of the field may be fostered by easier access to learning materials outside of traditional learning environments, tools to break down silos and allow various skill-sets to participate and drive data visualization creation, and the sprouting of digital communities for collaboration and troubleshooting.\n\n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":336,"value":"#### Years of experience in data visualization","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1099,"value":"surveyCompareBars(\n yearsOfExperience, \n \"Years of Experience\", \n [\"H2 '20\", \"H1 '21\"], \n [\"Dec. 2020 survey\", \"June 2021 survey\"],\n \"During each survey, 20 percent of the practitioners were new to the field.\"\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1148,"value":"---\n## Creators, not just consumers\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":166,"value":"Traditionally, analyzing and visualizing data was reserved for experts. Observable's community challenges this perspective. We see an overwhelming majority of our user population (including those that don't identify as data analysts or dataviz experts) using the platform to explore and analyze data, and create visualizations for the explanation and examination of complex topics.\n\n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":966,"value":"bigPercentageWithDescription(\n create[2][\"H1 '21\"] + create[3][\"H1 '21\"] + create[4][\"H1 '21\"],\n html`of respondents create data visualizations at least sometimes for the work they are completing`\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1182,"value":"surveyHistograms(create, \"Create data visualizations\", \"H1 '21\", false, [2, 3, 4])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1151,"value":"---\n## An overwhelming number of tools\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":59,"value":"The growing community of data practitioners is diverse, and it is no surprise they use a diverse set of tools. People are traditionally siloed by function or by role in their organizations. The different products people use reinforce the silos. As the data below shows, people use three, four, five, or more tools to stitch together an end-to-end flow to analyze, explore and communicate insights from their data.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2338,"value":"$2e","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":771,"value":"ToolsImage = longList(tools, \"unique tools reported, ordered by popularity\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2205,"value":"Data work dependent on many different tools is too slow, error-prone and frustrating. Constant *tool-hopping is not the way forward*. In order for data teams to work together effectively, we need to *break down the silos*. People who can collaborate without friction and make decisions quickly will have a huge business advantage. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":471,"value":"---\n## JavaScript isn’t just for web development","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":343,"value":"Javascript is the fastest growing language on the web. \n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1228,"value":"bigPercentageWithDescription(\njavascriptExperience[1][\"pct\"] + javascriptExperience[2][\"pct\"] + javascriptExperience[3][\"pct\"],\nhtml`of respondents are familiar with JavaScript to some degree`\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2203,"value":"Interestingly, *very few identify as front-end developers*. \n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1219,"value":"bigPercentageWithDescription(\nroles[1][\"pct\"],\nhtml`of respondents identify as
Front-end developer`\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2202,"value":"Every day, our users use JavaScript to explore and analyze data, build data visualizations, and develop using their data for more insights. We like to think the Observable platform makes these tasks easier.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1511,"value":"---\n## Data For The Win\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":123,"value":"While data workflows have increased in complexity and scope over the years, the data that people work with is mostly tabular. Databases and spreadsheets, that have been around for decades, still reign supreme.\n\n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":403,"value":"#### What types of data do you work with?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":422,"value":"surveyHistograms(dataTypes, \"Data type\", \"pct\", true, true)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2199,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2198,"value":"#### Multiple data sources","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2197,"value":"What is also interesting is the increase in the *number of data sources* being used to get the work done:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2032,"value":"bigPercentageWithDescription(\n dataSources[1][\"pct\"] + dataSources[2][\"pct\"] + dataSources[3][\"pct\"] + dataSources[4][\"pct\"],\n html`of respondents use multiple data sources at least occasionally`\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1842,"value":"surveyHistograms(dataSources, \"multiple\", \"pct\", false, [1, 2, 3, 4])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2196,"value":"This indicates another dimension of complexity that data practitioners have to deal with when trying to understand data and communicate information from that data. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":118,"value":"---\n\n## Collaboration is the norm","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2195,"value":"Collaboration is the price of admission given the way people work together in a highly-connected world.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1274,"value":"Collaboration = bigPercentageWithDescription(collaborationFrequency[1][\"pct\"] + collaborationFrequency[2][\"pct\"] + collaborationFrequency[3][\"pct\"],\nhtml`of respondents collaborate with others at least a quarter of the time`\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":125,"value":"
\nMore and more practitioners are leveraging data visualization for effective decision making in every domain. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1683,"value":"We notice that most of the reported collaboration is between two or three people. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":393,"value":"
\n#### How many people do you collaborate with?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":437,"value":"CollaborationPeople = surveyHistograms(numberCollaborators, \"Collaborators\", \"pct\", false, false)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2191,"value":"This indicates an increasing demand for live, synchronous collaboration to enable quick and effective data exploration for these types of tight-collaborative relationships.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":145,"value":"---\n## Conclusion","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":315,"value":"With data insights becoming increasingly important for businesses, there is an *emerging community of data practitioners* that is quickly growing and evolving beyond the traditional organizational silos. With the growth of this community, more and more cross-functional collaboration is happening every day to inform and drive data-based decision making. \n\nMoving forward, we expect data-based collaboration and decision-making to be the norm, shaping the markets in the data visualization, data analysis and business intelligence categories. We are listening to and learning from this data practitioner community, and reporting back on our findings!\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2157,"value":"md `---`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2006,"value":"We would like to thank the members of our community whose enthusiastic response made this report possible, along with the members of the Observable team who helped curate and deliver this report to the community. \n\nWe would love to include your voice in future reports, so please consider participating in our bi-annual surveys next time.\n\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2098,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1890,"value":"banner(\"Interested in collaborating with data?\", \"Explore the Observable Community\", \"https://observablehq.com/explore\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":155,"value":"md `\n
\n\n*For questions please reach out to [press@observablehq.com](press@observablehq.com)*\n
\n\n---`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":159,"value":"## Appendix\n\n
","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1657,"value":"### Methodology\n\nThis data was collected by the Observable team over the course of a year (H2 2020 and H1 2021) through the use of two demographic surveys (n=642 & n=572, respectively).\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1861,"value":"### References\n\n- [Data Visualization Market Size, Share and Industry Analysis. (2020, July)](https://www.fortunebusinessinsights.com/data-visualization-market-103259)\n- [How Much Data is Created Every Day? [27 Staggering Stats]. (2021, January)](https://seedscientific.com/how-much-data-is-created-every-day/)\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2027,"value":"md `---`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1557,"value":"### Imports","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":922,"value":"import {pieChart, surveyCompareBars, surveyHistograms, longList, bigPercentage, bigPercentageWithDescription} from \"cf42a44ac2f24b7a\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2105,"value":"import {banner} from \"@observablehq/brand-assets\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1560,"value":"### Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":452,"value":"create = d3.tsvParse(`Create data visualizations\tH2 '20\tH1 '21\nNever\t3.4\t2.5\nRarely\t20\t15.3\nSometimes\t32.9\t34.4\nOften\t30.7\t34.3\nAlways\t13\t13.5`, d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":383,"value":"roles = d3.tsvParse(`Role\tdataRole\tpct\tcount\nHobbyist\tsupport\t30.6\t174\nFront-end developer\tsupport\t14.2\t81\nAcademic or government researcher\tsupport\t14.2\t81\nData analyst or business analyst\tprimary\t9.65\t55\nData scientist\tprimary\t7.37\t42\nData architect\tprimary\t3.3\t19\nStudent\tsupport\t5.61\t32\nEducator\tsupport\t5.09\t29\nJournalist\tsupport\t2.98\t17\nOther\tsupport\t6.32\t39`, d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":333,"value":"yearsOfExperience = d3.tsvParse(`Years of Experience\tH2 '20\tH1 '21\n0 – 1 years\t20.1\t19.7\n1 – 3 years\t25.0\t25.8\n3 – 5 years\t19.8\t20.2\nMore than 5 years\t35.2\t34.3`, d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":407,"value":"collaborationFrequency = d3.tsvParse(`Frequency\tpct\n0-25% of the time\t58.7\n25-50% of the time\t24.5\n50-75% of the time\t9\n75-100% of the time\t7.7`, d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":767,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":408,"value":"numberCollaborators = d3.tsvParse(`Collaborators\tpct\n1 other person\t42.7\n2 other people\t42\n3 other people\t9.3\n4 other people\t2\n5 other people\t0.7\nMore than 5 others\t3.3`, (d) => {\n return {\n \"Collaborators\": d.Collaborators,\n \"pct\": +d.pct\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":419,"value":"dataTypes = d3.tsvParse(`Data type\tpct\nTabular\t51.7\nTemporal\t20.2\nNetwork\t13.3\nHierarchical\t5.5\nGeographical\t9.2`, d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":352,"value":"javascriptExperience = d3.tsvParse(`JavaScript experience\tpct\nNever used JavaScript\t5.6\nBeginner\t22.2\nIntermediate\t39.1\nAdvanced\t33.1`, d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":413,"value":"goals = d3.tsvParse(`Goal\tpct\nVisualize data to begin or continue data analysis\t18.3\nVisualize data to share with large groups\t16.5\nCreate visualizations or dashboards for executive stakeholders or clients\t7\nPrototyping visualizations or dashboards\t32.2\nCreate visualizations or dashboards that can be ported to other development environments\t9.5\nNone of the above\t16.5`, d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1837,"value":"dataSources = d3.tsvParse(`multiple\tpct\nNever\t20.2\nOccasionally\t37.1\nSometimes\t22.7\nOften\t16.2\nAlways\t3.8`, d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W30","stdlib":"1"}} 2d:"$2c:body"