Data Dictionary: Multi-source Employee API

on this page, you'll f ind detailed information about coresignal's multi source employee data each category includes a table listing the available data points, their explanations, data types, and sample code snippets all personal/company information mentioned within this context is entirely fictional and is solely intended for illustrative purposes data points in the example snippets are rearranged for better grouping data dictionary multi source employee api /#metadata data dictionary multi source employee api /#i dentifiers and urls data dictionary multi source employee api /#e mployee information data dictionary multi source employee api /#professional contact information data dictionary multi source employee api /#location data dictionary multi source employee api /#experience and workplace data dictionary multi source employee api /#active experience overview data dictionary multi source employee api /#active experience overview data dictionary multi source employee api /#skills data dictionary multi source employee api /#experience duration data dictionary multi source employee api /#full experience information data dictionary multi source employee api /#workplace details data dictionary multi source employee api /#metadata and firmographics data dictionary multi source employee api /#social media data dictionary multi source employee api /#financials data dictionary multi source employee api /#workplace locations data dictionary multi source employee api /#education data dictionary multi source employee api /#salary data dictionary multi source employee api /#projected base salary data dictionary multi source employee api /#projected additional salary data dictionary multi source employee api /#projected total salary data dictionary multi source employee api /#profile field changes data dictionary multi source employee api /#r ecent experience changes data dictionary multi source employee api /#r ecommendations data dictionary multi source employee api /#activity data dictionary multi source employee api /#awards data dictionary multi source employee api /#courses data dictionary multi source employee api /#certifications data dictionary multi source employee api /#languages data dictionary multi source employee api /#patents data dictionary multi source employee api /#publications data dictionary multi source employee api /#projects data dictionary multi source employee api /#organizations metadata data point description data type created at the date and time when the employee record was created string (date) updated at the date and time when the employee record was last fully updated string (date) checked at the date and time when the employee record was last checked partially string (date) changed at the date and time when the employee record was last changed string (date) experience change last identified at the date and time when the employee record change was last identified string (date) is deleted marks if the employee record is deleted or private 1 – the record is deleted 0 – the record is not deleted number (integer) is parent notes if the employee record is the main employee profile 1 – the record is parent (main) 0 – the record is not parent number (integer) see a snippet of the dataset for reference metadata "created at" "2024 07 27t01 56 27 000", "updated at" "2024 10 23t05 50 09 000", "checked at" "2025 10 23t05 50 09 000", "changed at" "2025 11 21t06 30 1 000", "experience change last identified at" "2024 10 25t06 30 10 000", "is deleted" 0, "is parent" 1 i dentifiers and urls data point description data type id coresignal's identification key for an employee profile record taken from the professional network dataset number (integer) parent id parent category identification key number (integer) historical ids historical identification keys that are related to the same profile after url change array of strings professional network url most recent profile url on professional network string professional network shorthand names historical variations of shorthand names for the employee array of strings public profile id public profile id number (long) see a snippet of the dataset for reference identifiers & urls "id" 12389891, "parent id" 12389891, "public profile id" 123456789, "historical ids" \[ 12389891, 11589843 ], "professional network url" "https //www professional network com/in/john doe 18729383", "professional network shorthand names" \[ "real john doe" "john doe 1992" ], e mployee information data point description data type full name employee's full name string first name employee's first name parsed from the full name string first name initial first name initial parsed from first name string middle name employee's middle name parsed from the full name string middle name initial middle name initial parsed from middle name string last name employee's last name parsed from the full name string last name initial last name initial parsed from last name string picture url picture url string connections count count of profile connections number (integer) followers count count of profile followers number (integer) interests employee's interests array of strings see a snippet of the dataset for reference employee information "full name" "john doe", "first name" "john", "first name initial" "j", "middle name" "michael", "middle name initial" "m", "last name" "doe", "last name initial" "d", "picture url" "https //static lnk com/aero v1/sc/h/9c8pery4andzj6ohjkjp54ma2" "connections count" 472, "followers count" 3190, "interests" \[ "hiking", "snowboarding", "cycling", ] professional contact information coresignal collects only publicly available , strictly business related data published or released by companies or individuals at their discretion online the contact information includes only professional emails no sensitive or private/ located within the login secured areas information is collected or transmitted data point description data type primary professional email employee's business email address tied to their workplace string primary professional email status the confidence level in the accuracy of the employee's business email address the field will return four options verified , matched email, matched pattern, or guessed common pattern string professional emails collection collection of employee's business email addresses array of structs professional email employee's business email address string professional email status the confidence level in the accuracy of the employee's professional email address the field will return four options verified – the email was matched and verified matched email – the email was matched but could not retrieve "verified" status matched pattern – the exact email was not matched, but it was guessed based on the matched email pattern for the company guessed common pattern – neither the exact email nor the email pattern for that company was matched, but the most common global pattern was guessed string order of priority order of priority based on confidence in email validity number (integer) see a snippet of the dataset for reference professional contact information "primary professional email" "johndoe\@company1 com", "primary professional email status" "matched pattern", "professional emails collection" \[ { "professional email" "johndoe\@company1 com", "professional email status" "matched pattern", "order of priority" 1 }, { "professional email" "john doe1\@company1 com", "professional email status" "matched pattern", "order of priority" 2 }, { "professional email" "johndoe123\@company1 com", "professional email status" "matched pattern", "order of priority" 3 } ] location data point description data type location country associated country string location country iso2 iso 2 letter code of the location country , based on their location country value string location country iso3 iso 3 letter code of the location country , based on their location country value string location full full location string location regions associated geographical regions based on their location country value array of strings see a snippet of the dataset for reference location "location country" "united states", "location country iso2" "us", "location country iso3" "usa", "location full" "san diego, california, united states", "location regions" \[ { "region" "americas" }, { "region" "northern america" }, { "region" "amer" } ] experience and workplace active experience overview data point description data type headline profile headline string summary main description (employee summary) string services offered services string is working marks if the employee is currently employed 1 – the employee is currently working 0 – the employee is currently not working number (integer) active experience company id coresignal's identification key for a company to identify where the employee is currently working number (integer) active experience title title of employee's current position string active experience description description of the current position string active experience department a list of employee's departments, based on actve position title string active experience management level a list of employee's management levels, based on active experience title string is decision maker marks if the employee is a decision maker, based on active experience title 1 – the employee is a decision maker 0 – the employee is not a decision maker number (integer) see a snippet of the dataset for reference active experience overview "headline" "data analyst | machine learning enthusiast", "generated headline" "data specialist – predictive analytics", "summary" "\<p>passionate about uncovering insights from data and applying machine learning techniques to solve global problems \</p>", "services" "data analysis, machine learning consulting, business intelligence", "is working" 1, "active experience company id" 4127532, "active experience title" "senior data analyst", "active experience description" "leading data driven projects, building predictive models, and optimizing business intelligence strategies ", "active experience department" "engineering and technical", "active experience management level" "senior", "is decision maker" 1 skills data point description data type inferred skills lists employees' skills based on the descriptions from the profile array of strings historical skills historical skills array of strings see a snippet of the dataset for reference skills "inferred skills" \[ "cloud computing", "data analysis", "deep learning", "software development", "system architecture", "troubleshooting", "web development" ] experience duration data point description data type data type total experience duration months total experience duration months total normalized experience duration of all employee's experiences total normalized experience duration of all employee's experiences number (integer) number (integer) total experience duration months breakdown department total experience duration months breakdown department total normalized experience duration by employee's department total normalized experience duration by employee's department array of structs array of structs department department department department string string total experience duration months total experience duration months experience duration in months experience duration in months string string total experience duration months breakdown management level total experience duration months breakdown management level total normalized experience duration by employee's management level total normalized experience duration by employee's management level array of structs array of structs management level management level employee's management level employee's management level string string total experience duration months total experience duration months experience duration in months experience duration in months string string see a snippet of the dataset for reference experience duration "total experience duration months" 85, "total experience duration months breakdown department" \[ { "department" "c suite", "total experience duration months" 13 }, { "department" "marketing", "total experience duration months" 30 }, { "department" "finance & accounting", "total experience duration months" 14 }, { "department" "engineering and technical", "total experience duration months" 28 } ], "total experience duration months breakdown management level" \[ { "management level" "c level", "total experience duration months" 10 }, { "management level" "intern", "total experience duration months" 3 }, { "management level" "senior", "total experience duration months" 4 }, { "management level" "specialist", "total experience duration months" 40 }, { "management level" "manager", "total experience duration months" 18 } ] full experience information data point description data type experience work experience the employee has array of structs active experience identifies if this is a current (active) position string position title employee's position title string department employees department string management level employee's management level string location job/workplace location string date from employment start date string (date) date from year employment start year integer date from month employment start month integer date to employment end date string (date) date to year employment end year integer date to month employment end month integer duration months employment duration in months integer description employment description string see a snippet of the dataset for reference full experience information "experience" \[ { "active experience" 0, "position title" "senior data analyst", "department" "data science", "management level" "mid level", "location" "san francisco, california, united states", "date from" "march 2020", "date from year" 2020, "date from month" 3, "date to" "july 2022", "date to year" 2022, "date to month" 7, "duration months" 126 } ] workplace details metadata and firmographics data point description data type company id company record identification key in coresignal's database integer company name company name string company type company t ype string company founded year founding year string (date) company size range company size based on employee count range (as selected by the company profile administrator) string company employees count number of employees that associated their experience with the company number (integer) number (integer) company categories and keywords c ategories and keywords are assigned to the company profile and products across various platforms array of strings company employees count change yearly percentage company employee count change (percentage) number (integer) number (integer) company industry company's industry string company last updated at the last update date of the record in the yyyy mm dd format string (date) company is b2b company is b2b indicates if the company operates in a business to business model 1 – b2b company 0 – b2c company number (integer) number (integer) order in profile the order number of the workplace in the profile number (integer) number (integer) see a snippet of the dataset for reference metadata & firmographics "company id" 87272276, "company name" "company123, llc", "company type" "privately held", "company founded year" "2023", "company size range" "51 200 employees", "company employees count" 157, "company categories and keywords" \[ "data analysis", "ai", "management", "consulting", ], "company employees count change yearly percentage" 17 43222222222222 "company industry" "manufacturing", "company last updated at" "2025 02 03", "company is b2b" 1, "order in profile" 1 social media data point description data type company followers count company's profile follower count on professional network integer company website c ompany's website string company facebook url c ompany's facebook url array of s trings company twitter url c ompany's x (twitter) url array of s trings company linkedin url c ompany's linkedin url string see a snippet of the dataset for reference social media "company followers count" 527712, "company website" "https //www company1 com", "company facebook url" \[ "https //www facebook com/company1global", "https //www facebook com/company1" ], "company twitter url" \[ "https //www x com/company1" ], "company linkedin url" "https //www linkedin com/company/company1" financials data point description data type company annual revenue source 1 company annual revenue source 5 company's revenue from a specific source array of o bjects company annual revenue currency source 1 company annual revenue currency source 5 revenue currency string company last funding round date date when the last funding round was announced in yyyy mm dd format string (date) company last funding round amount raised amount raised in the last funding round integer (long) company stock ticker company's stock ticker information array of objects exchange stock exchange string ticker stock ticker string see a snippet of the dataset for reference financials "annual revenue source 5" 32590000, "annual revenue currency source 5" "$", "annual revenue source 1" 878728373, "annual revenue currency source 1" "$", "company last funding round date" "2014 03 25", "company last funding round amount raised" 200 000, "stock ticker" \[ { "exchange" "nasdaq", "ticker" "aapl" } ] workplace locations data point description data type company hq full address full address of the company's headquarters string company hq country the c ountry where the company's headquarters is located string company hq regions detailed region where the company's headquarters is located array of strings company hq country iso2 iso 2 letter code of the headquarters country string company hq country iso3 iso 3 letter code of the headquarters country string company hq city headquarters city string company hq state headquarters state string company hq street headquarters street address string company hq zipcode headquarters zip code string see a snippet of the dataset for reference locations "company hq full address" "123 data drive, analytics city, ca 94016, usa", "company hq country" "united states", "company hq regions" \[ "americas", "northern america", "amer"], "company hq country iso2" "us", "company hq country iso3" "usa", "company hq city" "analytics city", "company hq state" "california", "company hq street" "123 data drive", "company hq zipcode" "94016", education data point description data type last graduation date last graduation date string (date) education degrees list of education degrees held by the person array of strings education employee's education array of objects degree degree name string description degree description string institution url institution's profile url string institution name institution's name string institution full address institution's full address string institution country iso2 iso 2 letter code of the institution's country string institution country iso3 iso 3 letter code of the institution's country string institution regions institution's region array of strings institution city institution's city string institution state institution's state string institution street institution's street string institution zipcode institution's zip code string date from year enrollment date number (integer) date to year graduation date string (date) activities and societies activities and societies that are connected with the employee string order in profile order in profile number (integer) see a snippet of the dataset for reference education "last graduation date" 2022, "education degrees" \[ "bachelor of science, computer science engineering, 9 12 (rank 4/80)", "senior secondary, mathematics, 93%", "higher secondary, science, 96%" ], "education" \[ { "degree" "bachelor of science, computer science engineering, 9 12 (rank 4/80)", "description" "focused on core sciences with a strong foundation in physics and chemistry ", "institution url" "https //www topuniversity edu", "institution name" "top university", "institution full address" "top university, 123 main st, cityville, state 12345, usa", "institution country iso2" "us", "institution country iso3" "usa", "institution regions" \[ "north america", "east coast" ], "institution city" "cityville", "institution state" "state", "institution street" "123 main st", "institution zipcode" "12345", "date from year" 2014, "date to year" 2016, "activities and societies" "science fair, debate team", "order in profile" 1 }, ] salary projected base salary data point description data type projected base salary p25 minimum projected base salary for the current position (25th percentile) number (double) projected base salary median median projected base salary for the current position number (double) projected base salary p75 maximum projected base salary for the current position (75th percentile) number (double) projected base salary period data collection period string projected base salary currency salary currency string projected base salary updated at data last update date string (date) see a snippet of the dataset for reference projected base salary "projected base salary p25" 105432 56, "projected base salary median" 120785 90, "projected base salary p75" 145430 78, "projected base salary period" "annual", "projected base salary currency" "usd", "projected base salary updated at" "2025 02 03" projected additional salary data point description data type projected additional salary projected additional salary array of structs projected additional salary type projected additional salary type for the current position string projected additional salary p25 minimum projected additional salary for the current position (25th percentile) number (double) projected additional salary median median projected additional salary for the current position number (double) projected additional salary p75 maximum projected additional salary for the current position (75th percentile) number (double) projected additional salary period data collection period string projected additional salary currency salary currency string projected additional salary updated at data last update date string (date) see a snippet of the dataset for reference projected additional salary "projected additional salary" \[ { "projected additional salary type" "cash bonus", "projected additional salary p25" 7654 21, "projected additional salary median" 10234 56, "projected additional salary p75" 14123 78 }, { "projected additional salary type" "stock bonus", "projected additional salary p25" 8892 10, "projected additional salary median" 11754 93, "projected additional salary p75" 16123 12 } ] "projected additional salary period" "annual", "projected additional salary currency" "usd", "projected additional salary updated at" "2024 12 06" projected total salary data point description data type projected total salary p25 minimum projected total salary value for the current position (25th percentile) number (double) projected total salary median median projected total salary value for the current position number (double) projected total salary p75 maximum projected total salary value for the current position (75th percentile) number (double) projected total salary period data collection period string projected total salary currency salary currency string projected total salary updated at data last update date string (date) see a snippet of the dataset for reference projected total salary "projected total salary p25" 142763 21, "projected total salary median" 153290 88, "projected total salary p75" 165432 19, "projected total salary period" "annual", "projected total salary currency" "usd", "projected total salary updated at" "2025 02 12", profile field changes data point description data type profile root field changes summary summary of the field level changes array of structs field name name of the data field string change type type of the data field change string last changed at date of the last data field change string (date) profile collection field changes summary summary of changes in profile collection fields array of structs field name name of the collection data field string last changed at data of the last collection data field change string see a snippet of the dataset for reference profile field changes "profile root field changes summary" \[ { "field name" "followers count", "change type" "updated", "last changed at" "2023 07 18t09 22 45 567" }, { "field name" "summary", "change type" "updated", "last changed at" "2025 02 18t09 22 45 567" } ], "profile collection field changes summary" \[ { "field name" "experience", "last changed at" "2024 01 05t17 48 12 892" }, { "field name" "activity", "last changed at" "2025 02 05t17 48 12 892" } ] r ecent experience changes data point description data type experience recently started experience recently started collection of identified recently started employee experiences collection of identified recently started employee experiences array of structs array of structs company id company id coresignal's identification key for a company record coresignal's identification key for a company record string company name company name company name company name string company url company url url of the company url of the company string company shorthand name company shorthand name shorthand name of the company's url shorthand name of the company's url string date from date from start date of the experience record start date of the experience record string date to date to end date of the experience record end date of the experience record string title title position title in the company position title in the company string identification date identification date date when experience change was identified date when experience change was identified string experience recently closed experience recently closed collection of employee experiences collection of employee experiences that ended recently array of structs array of structs company id company id coresignal's identification key for a company record coresignal's identification key for a company record string company name company name company name company name string company url company url url of the company url of the company string company shorthand name company shorthand name shorthand name of the company's url shorthand name of the company's url string date from date from start date of the experience record start date of the experience record string date to date to end date of the experience record end date of the experience record string title title position title in the company position title in the company string identification date identification date date when experience change was identified date when experience change was identified string see a snippet of the dataset for reference recent experience changes "experience recently started" \[ { "company id" 3124502, "company name" "company1, llc", "company url" "https //www professional network com/company/company1 llc", "company shorthand name" "company1 llc", "date from" "nov 2024", "date to" "dec 2024", "title" "senior software engineer", "identification date" "2024 11 19t15 34 29 412" }, ], "experience recently closed" \[ { "company id" 3124504, "company name" "company3, llc", "company url" "https //www professional network com/company/company3 llc", "company shorthand name" "company3 llc", "date from" "jul 2021", "date to" "oct 2024", "title" "software engineer", "identification date" "2024 12 14t10 48 37 215" } ] r ecommendations data point description data type recommendations count number of recommendations from other users number (integer) recommendations list of recommendations received array of structs recommendation recommendation text string referee full name the full name of the person who wrote the recommendation string referee url the url of the profile of the person who wrote the recommendation string order in profile the exact position of the recommendation in the profile number (integer) see a snippet of the dataset for reference recommendations "recommendations count" 2, "recommendations" \[ { "recommendation" "“i had the pleasure of collaborating with john during his time at tech innovations, where he displayed a rare combination of creativity and technical expertise he consistently demonstrated outstanding problem solving skills, particularly in software engineering and ai his attention to detail and collaborative spirit made him a valuable asset to the team john is also a great mentor who is always ready to share his knowledge with others, making him a true team player ”", "referee full name" "jane doe 1", "referee url" "https //www professional network com/in/jane doe 1", "order in profile" 1 }, { "recommendation" "“john’s drive and determination have impressed me from our first interaction during a project at company1 solutions he has an extraordinary ability to tackle complex challenges and has a passion for both technology and team collaboration his contributions were key to the success of several high profile projects he is an individual who thrives in dynamic environments and continuously seeks to innovate and improve processes ”", "referee full name" "jane doe 2", "referee url" "https //www professional network com/in/jane doe 2", "order in profile" 2 } ] activity data point description data type activity user's activity (posts) array of structs activity url post url string title post title string action activity type string order in profile the exact position of the activity in the profile number (integer) see a snippet of the dataset for reference activity "activity" \[ { "activity url" "https //www professional network com/posts/johndoe ai innovations and the future of tech activity 1234567890123456789 xyz", "title" "excited to share my thoughts on the future of ai and its impact on industries worldwide the advancements in machine learning are opening new doors…", "action" "liked by", "order in profile" 1 } ] awards data point description data type awards awards held by the person array of structs title award title string issuer award issuer string description award description string date award date string date year award year stringnumber (integer) date month award month number (integer) order in profile the exact position of the award in the profile number (integer) see a snippet of the dataset for reference awards "awards" \[ { "title" "outstanding achievement award", "issuer" "top university", "description" "recognized for exceptional contributions to student initiatives and leadership in organizing university wide events ", "date" "march 15, 2024", "date year" 2024, "date month" 3, "order in profile" 1 } ] courses data point description data type courses courses a rray of structs organizer course organizer s tring title course t itle s tring order in profile the exact position of the course in the profile n umber (integer) see a snippet of the dataset for reference courses "courses" \[ { "organizer" "ai certification", "title" "machine learning fundamentals", "order in profile" 1 }, { "organizer" "cs academ", "title" "advanced algorithms and data structures", "order in profile" 2 }, ] certifications data point description data type certifications certifications a rray of structs title certification title s tring issuer certification i ssuer s tring issuer url issuer profile url s tring credential id credential identification key s tring certificate url certification url s tring date from certification issue date s tring (date) date from year issue year n umber (integer) date from month issue month n umber (integer) date to certification expiry date s tring (date) date to year expiry year n umber (integer) date to month expiry month n umber (integer) order in profile the exact position of the certification in the profile n umber array see a snippet of the dataset for reference certifications "certifications" \[ { "title" "advanced data analysis", "issuer" "certification company 123", "issuer url" "https //www certificationcompany123 com", "credential id" "efgh98765432", "certificate url" "https //www certificationcompany123 com/certificates/f44f9027fba14efb953da9db849e5ed2", "date from" "nov 2023", "date from year" 2023, "date from month" 11, "date to" "nov 2024", "date to year" 2024, "date to month" 11, "order in profile" 1 } ] languages data point description data type languages language knowledge a rray of structs language listed l anguage s tring proficiency language proficiency s tring order in profile the exact position of the language in the profile n umber (integer) see a snippet of the dataset for reference languages "languages" \[ { "language" "english", "proficiency" "full professional proficiency", "order in profile" 1 }, { "language" "spanish", "proficiency" "limited working proficiency", "order in profile" 2 }, { "language" "french", "proficiency" "professional working proficiency", "order in profile" 3 } ] patents data point description data type patents count number of authored patents n umber (integer) patents topics patent topics array of strings patents authored patents a rray of structs title patent title s tring status patent status s tring description patent description string patent url patent url string date patent filing date s tring (date) date year filling year n umber (integer) date month filling month n umber (integer) patent number patent number string order in profile the exact position of the patent in the profile n umber (integer) see a snippet of the dataset for reference patents count "patents count" 1, "patents topics" "data analysis", "patents" \[ { "title" "advanced data analysis using neural networks", "status" "granted", "description" "a novel approach to data analysis leveraging deep learning techniques to improve accuracy in predictive modeling and data interpretation \\\n\<! > \</p>", "patent url" "https //example123 com/patent/data analysis neural networks", "date" "september 10, 2023", "date year" 2023, "date month" 9, "patent number" "us112233445a1", "order in profile" 1 } ] publications data point description data type publications count count of publications authored by the employee number (integer) publications topics publication topics array of strings publications authored publications a rray of structs title publication title st ring description publication description st ring publication url publication website url st ring publisher name publication publisher array of strings date publication release date st ring (date) date year release year number (integer) date month release month number (integer) order in profile the exact position of the publication in the profile number (integer) see a snippet of the dataset for reference publications "publications count" 1, "publications topics" \[ "machine learning in healthcare applications" ], "publications" \[ { "title" "machine learning based heart disease prediction", "description" "this research focuses on utilizing machine learning techniques to predict heart diseases by analyzing ekg signals, a part of my project from june'21 to december'21 \\\n\<! > \</p>", "publication url" "https //www researchpaper123 net/publication/343632915 machine learning", "publisher names" \[ "john doe", "jane doe" ], "date" "december 15, 2021", "date year" 2021, "date month" 12, "order in profile" 1 } ] projects data point description data type projects count count of total projects listed in the profile nu mber (integer) projects topics topics related to the projects listed in the profile array of strings projects projects created by the profile a rray of structs name project name s tring description project description s tring project url project website url s tring date from project start date s tring (date) date from year project start year nu mber (integer) date from month project start month nu mber (integer) date to project end date s tring (date) date to year project end year nu mber (integer) date to month project end month nu mber (integer) order in profile the exact position of the project in the profile nu mber (integer) see a snippet of the dataset for reference projects "projects count" 1, "projects topics" \[ "predictive analytics in complex systems", "real time facial expression analysis for emotional intelligence systems", "design and simulation of adaptive actuators for smart materials", "audio signal separation for enhanced speech recognition", "non invasive glucose monitoring using spectroscopic data analysis" ], "projects" \[ { "name" "predictive analytics for fault detection in complex mechanical systems", "description" "as part of a research initiative, a predictive system was developed to identify anomalies in mechanical systems the project utilized historical failure data and machine learning models \</p>", "project url" "https //www projecturl123 net/project/123456 analytics", "date from" "oct 2018", "date from year" 2018, "date from month" 10, "date to" "may 2019", "date to year" 2019, "date to month" 5, "order in profile" 1 } ] organizations data point description data type organizations memberships in organizations a rray of structs organization name organization title s tring position position in the organization s tring description description of the activity/experience in the organization s tring date from membership start date s tring (date) date from year membership start year n umber (integer) date from month membership start month n umber (integer) date to membership end date s tring (date) date to year membership end year n umber (integer) date to month membership end month n umber (integer) order in profile the exact position of the organization in the profile n umber (integer) see a snippet of the dataset for reference organizations "organizations" \[ { "organization name" "tech club", "position" "event coordinator", "description" "led and organized data driven workshops and events, focusing on data analytics and machine learning applications in various industries ", "date from" "feb 2016", "date from year" 2016, "date from month" 2, "date to" "mar 2018", "date to year" 2018, "date to month" 2, "order in profile" 1 } ]