Databases Projects

opportunity

Scraping data from the internet

I am looking for an experienced web scraping professional to extract structured data from a UK school directory site. The target website is the Independent Schools Council (ISC) directory. An example of the exact page structure can be found here: https://www.isc.co.uk/schools/england/berkshire/newbury/cheam-school/ There are approximately 1,600 similar school profile pages across this directory structure. Please note that the exact number is unverified, so your initial task will involve crawling/mapping the total number of profile URLs to confirm the final scope. Data Requirements: I need the following data points for each school: - School Name - Postcode - Total Size (Number of pupils) - Total number of Day Boys (this is the number in brackets) - Total number of Boarding Boys (this is the number in brackets) - Total number of Day Girls (this is the number in brackets) - Total number of Boarding Girls (this is the number in brackets) - Boarding fees per term (lowest number) - Boarding fees per term (Highest number) - Day fees per term (lowest number) - Day fees per term (Highest number) Deliverables: A clean, well-formatted Excel (.xlsx) file. Each school should be a row, and each data point listed above should be a clearly labelled column. Ability to handle missing data fields gracefully without breaking the spreadsheet structure (some schools may not list all fields). Good communication skills to confirm the final page count before executing the full script. Many thanks

MS SQL EXPERT NEEDED (USA BASED ONLY)

As an expert, you must be residing in the USA, be able to provide a W9 tax form as a consultant, and sign an NDA. The project involves analyzing a complex MS SQL database with over 1500 tables in order to dump and convert the raw data tables into MySQL. The backup is nearly 15GB of data. The schema is based on Enspire ERP and requires the ability to identify which tables are joined in order to output relevant archive data. You will work together to provide samples of what data fields are identified and narrow down only those which are required. Many system fields are likely and not needed, so it will be a process of working together to adequately arrive at a curated MySQL database. Migration of resulting data will be part of the process onto a Linux cloud server with MySQL installed. Project will be awarded based on best overall estimated total hours to complete.

opportunity

(Phase 2, inspection results) SAP Workflow

Dear Maria, We would like to continue the project and integrate another process into the system. This time, we would like to integrate incoming inspection results. Best Regards Carp

Create automated planning application spreadsheet

I am looking for someone to create an automated spreadsheet/report that pulls the previous week’s UK planning applications from the UK PlanIt data/API. The purpose of the report is to help identify potential trade opportunities for builders, loft conversion companies, kitchen/renovation firms, roofers and other home improvement trades. I need the spreadsheet to be refreshable each week, so I can update it with the latest planning applications and then export or share the data with ChatGPT for analysis. What I need is a spreadsheet system, ideally in Google Sheets or Excel, that can: 1. Pull planning application data from UK PlanIt. 2. Refresh the report weekly to show the previous 7 days of applications. 3. Cover all UK counties / planning areas, not just one local authority. 4. Handle multiple planning authorities within each county where needed. 5. Pull clean, structured data into a spreadsheet. 6. Allow me to filter by county, planning authority, date, application type and likely trade opportunity. 7. Create summary tabs that make the data easy to review. 8. Be simple enough for a non-technical user to refresh each week. **Important functionality required:** The spreadsheet should include: * A refresh button or clear refresh process. * A date range selector, ideally defaulting to the last 7 days. * County / area filtering. * Planning authority filtering. * Keyword filtering for relevant trade opportunities. * Automatic categorisation where possible, for example: * Extensions * Loft conversions * Garage conversions * Renovations/refurbishments * Kitchens * Roofing * Outbuildings * Commercial fit-outs * Other building works * A clean export tab that can be copied into ChatGPT for analysis. * Basic error handling if the API limit is reached or if a request fails. * A simple instruction tab explaining how I refresh and use the report. **Suggested spreadsheet tabs:** 1. **Instructions** Simple user guide explaining how to refresh the data and use the spreadsheet. 2. **Settings / Control Panel** Date range, counties/areas to include, keywords, refresh controls and any API settings. 3. **Raw Planning Applications** The unedited data pulled from PlanIt. 4. **Cleaned Applications** Clean version of the data with standardised columns. 5. **Trade Categorisation** Applications categorised by likely trade relevance. 6. **County Summary** Number of opportunities by county and trade type. 7. **Planning Authority Summary** Number of opportunities by local authority. 8. **ChatGPT Export** A clean tab designed specifically so I can copy/export the data and ask ChatGPT to analyse it. **Required data fields:** Where available from PlanIt, I would like the spreadsheet to include: * Application name/reference * Planning authority * County / area * Application start date * Address * Description * Application type * Development type * Status * Decision, if available * Applicant / agent details, if available * Link to planning application * Latitude / longitude, if available * Last scraped / last changed date * Suggested trade category * Opportunity score, if possible **Trade opportunity scoring:** Ideally, I would like a simple scoring system to highlight the best opportunities. For example: * High relevance: extension, loft conversion, conversion, major renovation * Medium relevance: alterations, outbuildings, roof works, garage conversion * Low relevance: tree works, signage, minor admin applications, discharge of conditions I am happy for the freelancer to suggest the best scoring approach. **Technical requirements:** The freelancer should be comfortable working with: * APIs * Google Sheets Apps Script and/or Excel Power Query * CSV/JSON data imports * Pagination * Rate limits * Data cleaning * Building refreshable dashboards/reports The PlanIt API has paging and request limits, so the system must be built responsibly and should not rely on one huge request. **End goal:** Each week I want to be able to refresh the spreadsheet, see the latest planning applications across all counties, identify the best trade opportunities, and then ask ChatGPT to analyse the data by county, trade type and opportunity quality. **Deliverables:** 1. A working Google Sheet or Excel workbook. 2. Automated or semi-automated weekly refresh process. 3. All required tabs and filters. 4. Clean data structure ready for ChatGPT analysis. 5. Simple instructions for use. 6. A short handover call or written walkthrough. 7. Notes on any limitations of the PlanIt API or recommended future improvements. **Please include in your response:** * Whether you recommend Google Sheets or Excel for this. * Examples of similar API/spreadsheet automation work. * How you would handle all counties and multiple planning authorities. * How you would manage API limits and pagination. * Estimated delivery time. * Fixed price quote.

App based KPI Dashboard

Hi I am developing a company KPI scorecard for our property investment company and we are currently inputting data into an excel spreadsheet and I am hoping this can then be developed into a dashboard for board meetings. My intial though is to use Microsoft Power Apps as we are on MS 365 / Teams etc. Hoping someone can help Thanks

opportunity

Python Developer Needed to Build Product Rotation Algorithm

"Big Al" - Tiktok Live Algorithm Project Overview I am looking for a Python developer to build a product rotation and sales-tracking algorithm called Big AL for my football-themed business, Top Binz. Big AL will be used to organise TikTok Live selling sessions. Each TikTok Live will feature: 11 player fanart t-shirt designs 11 signed player print designs The goal is to make every Live different, avoid unnecessary duplication, give every design fair exposure, and use sales data to identify best sellers and the strongest buying times. The best-performing products will later be used to improve my Shopify store collections and product promotion. Main Goal Build a Python-based system that can automatically generate TikTok Live product sets based on product IDs, performance data, availability, and rotation rules. The system should help answer: Which t-shirt designs should appear in the next Live? Which signed prints should appear in the next Live? Which products have not been shown enough? Which products are best sellers? Which players, categories, and time slots perform best? Which products should be pushed onto Shopify as winners? Product Structure Each individual design will have its own unique ID. Example t-shirts: TEE-0001 — Zidane Design 1 TEE-0002 — Zidane Design 2 TEE-0003 — Messi Design 1 Example prints: PRT-0001 — Zidane Signed Print PRT-0002 — Messi Signed Print PRT-0003 — Ronaldinho Signed Print The algorithm should treat every design as its own product, not just group everything by player. Required Features 1. Product Database The system should allow me to store and manage: Product ID Product type: T-shirt or signed print Player name Design name Category, such as Brazil, Argentina, Premier League, France, GOAT, etc. Stock quantity Status: Active, New, Hot, Cold, Retired Number of times shown in Lives Sales Revenue Last shown date/time 2. TikTok Live Set Generator The system must generate a Live set containing: 11 unique t-shirt IDs 11 unique signed print IDs Each Live should avoid: Duplicate products in the same Live Repeating the same products too often Showing out-of-stock or retired products Overloading one Live with too many designs from the same player, unless allowed 3. Rotation Rules The algorithm should be able to follow rules such as: Prioritise designs that have never been shown Prioritise designs with low appearances Include a small number of proven best sellers Include some new or test designs Avoid products that appeared in the most recent Lives Keep each Live fresh and different A suggested starting structure is: 60% new or low-exposure products 30% proven performers 10% wildcard/test products This should apply separately to t-shirts and prints. 4. Performance Scoring The system should score each product based on performance. Useful metrics include: Total sales Revenue Sales per appearance Conversion rate if views/clicks are entered Average sales by day Average sales by time slot Last shown date Stock remaining Example score: Sales per appearance = total sales ÷ number of Live appearances The scoring system should help classify products as: New Rising Hot Average Cold Retired 5. Live Results Tracking After each TikTok Live, I need to be able to enter results such as: Live ID Date Time Product IDs shown Views if available Clicks if available Sales Revenue Notes This data should update future product selections. 6. Calendar / Schedule Generator The system should support a schedule of: 5 days per week 3 Lives per day 45 Lives per week 11 t-shirts and 11 prints per Live The algorithm should be able to generate a weekly schedule while keeping products fairly rotated and avoiding duplication where possible. 7. Shopify Winner Output The system should be able to export or identify products for Shopify, including: Best sellers Trending products Products with strong conversion Products that should be featured on the homepage Products that should be tagged as TOP_TIER, TRENDING, HOT, or LOW_TIER A CSV export would be useful for future Shopify product tagging. 8. Dashboard / Reports The system should generate simple reports showing: Top-selling t-shirts Top-selling prints Best-performing players Best-performing categories Best days for sales Best time slots for sales Products that need more exposure Products that should be retired or redesigned

opportunity

I need a Excel Dashboard creating

I am looking for an Excel/Power Query/VBA specialist to build a planning application lead-generation workbook using the UK PlanIt data https://www.planit.org.uk (https://www.planit.org.uk/api/) The workbook needs to let me click a button each week to pull the last 7 weeks of planning applications from all councils/planning authorities in Great Britain via the UK PlanIt API. Core requirements: 1. Data Import * Connect to the UK PlanIt API. * Pull applications from all active planning authorities/councils in Great Britain. * Use paging properly so results are not missed. * Respect API rate limits. * Pull new, changed and decided applications where possible. * Store the raw imported data in a master table. 2. Refresh Button * Add a simple “Refresh Planning Data” button. * When clicked, it should update the master data table. * Avoid duplicating applications already imported. * Keep a log of refresh date, number of records pulled, errors and skipped records. 3. Data Enrichment Columns Add calculated/enriched fields such as: * Project category * Builder opportunity: Yes/No * Roofer opportunity: Yes/No * Electrician opportunity: Yes/No * Plumber opportunity: Yes/No * Landscaper opportunity: Yes/No * Architect opportunity: Yes/No * Estimated project value range * Lead rating: Hot/Warm/Cold * Opportunity score 1–10 * Planning stage * Contact timing * Recommended action 4. Filters / Subscriber Views I need a way to filter the master data so different subscribers can only see opportunities relevant to: * Their trade type, e.g. builder, roofer, architect, electrician * Their subscribed area/council/postcode radius * Their lead rating, e.g. Hot only * Their project type, e.g. extensions, loft conversions, new builds Ideally, I would like a controlled output sheet where I can select a subscriber name and the workbook generates only the records they are allowed to see. 5. Data Protection / Access Control I need advice on the best way to protect the wider data so subscribers cannot access the full master database. Please advise whether this can be safely done in Excel, or whether separate exported workbooks/reports should be generated per subscriber. 6. Output Reports The workbook should be able to create/export: * A full internal master report * A filtered subscriber report * Trade-specific sheets * Area-specific sheets * Weekly opportunity summary 7. Dashboard Create a dashboard showing: * Total applications imported * Hot leads * Warm leads * Cold leads * Applications by council * Applications by trade opportunity * Estimated project value * New/changed/decided applications * Refresh status 8. Future Proofing Please build this in a way that can later connect to AI/ChatGPT enrichment, where application descriptions can be summarised and scored automatically. Important: The workbook must be reliable, repeatable and easy for a non-technical user to operate each week. Please also advise whether Excel is the right tool for this, or whether the data import and subscriber filtering should eventually sit in a database or web app.

opportunity

GoCardless to WooCommerce Subscription Migration

We have heating and renewables company with 1,000+ customers on recurring subscriptions. Around half of subscribers were signed up directly in GoCardless by office staff, so they exist outside WooCommerce. We want to migrate these subscribers into WooCommerce so all plans are managed from one place with collections continuing against their existing Direct Debit mandates. We want to avoid any customer re-authorisation or new mandates and ensure no double billing occurs. Scope of Work: 1) Extract subscribers from GoCardless 2) Differentiate those set up only through GoCardless 3) Clean the data and remove duplicates, leaving one row per subscription 4) Identify each plan, amount, and billing frequency (monthly or annual) 5) Confirm how WooCommerce links a subscription to an existing GoCardless mandate 6) Import subscribers into WooCommerce with their existing mandate details 7) Test a renewal on staging to confirm payment collects without a new mandate 8) Migrate in small batches and verify each one 9) Cancel the old GoCardless schedules once WooCommerce is collecting, avoiding double billing

opportunity

Structured Data Verifier / Research Assistant

Seeking a Structured Data Verifier / Research Assistant to compile accurate source URLs, required documents, processing times, and basic eligibility criteria for Canadian relocation pathways. Candidate will populate a provided template with verified, up-to-date information across multiple programs, ensuring consistency, proper citation formatting, and clear, concise entries. Attention to detail, reliable research skills, and familiarity with immigration resources are essential. Timely delivery and data integrity required.

opportunity

Scrape Muay Thai and Kickboxing gyms in European countries

I need a Google Scrape of every Muay Thai and Kickboxing gym in the following countries: Netherlands Germany Poland Italy Belgium France Spain Portugal UK Denmark Sweden Norway Czechia Austria Switzerland Data must include company name, address, phone number and email address.

Companies House Data Research & Database Creation Specialist

Overview I’m looking for a freelancer to build a structured database of founder-led UK businesses using Companies House data. The output will be used for business development and market analysis within technology, consulting, cyber security, MSP and SaaS sectors. This is a one-off project with potential for future enrichment work. Deliverables Create a Google Sheet containing: Company Information * Company Name * Company Number * Company Status * Incorporation Date * SIC Code(s) * Registered Location * Registered Country Ownership Information * Person with Significant Control (PSC) * PSC Type * Date Appointed (if available) Data Quality * Remove dissolved companies * Remove duplicate companies * Remove duplicate PSC records Filtering Requirements Include only: * Active companies * UK registered companies * Relevant SIC codes covering: * IT Services * Technology Consulting * Cyber Security * Managed Services * Software Development * SaaS-related businesses Exclude: * Dormant companies * Dissolved companies * Non-trading entities where identifiable Success Criteria Looking for: * Minimum 10,000 records * Accurate PSC linkage * Clean dataset * Clear methodology documentation Nice to Have (Optional Quote) Please provide separate pricing for: * Website identification * LinkedIn company page identification * Founder LinkedIn identification * Employee count enrichment * Revenue estimate enrichment These are not required for Phase 1. Questions for Applicants 1. Have you worked with Companies House bulk data or API before? 2. How would you identify founder-led companies using PSC data? 3. What tools would you use? 4. Can you provide an example of a similar dataset? 5. How many records could you deliver?

Database Build for Canada Relocation Pathways

Seeking a meticulous researcher to compile comprehensive relocation and visa pathways for Canada. You will identify, verify, and document all federal and provincial immigration streams, eligibility criteria, processing times, fees, required documents, and applicable restrictions. Tasks include thorough online research, accurate data entry into provided spreadsheet templates, and assembly of credible citations and source links. Strong attention to detail, proficiency with spreadsheets, and experience in immigration research or government-source navigation are essential.

Smartsheet → Google Sheets Migration (incl. forms & history)

We are looking for an experienced freelancer to migrate a set of Smartsheets into Google Sheets, including associated web forms, sheets and historical data. We need someone who understands both platforms and can ensure the structure, functionality, and data integrity are maintained throughout.

opportunity

SAP Workflow Automation with AI Agents

Dear Freelancer, We are seeking a concept for automating vendor invoice processing in SAP. Today, invoices are manually reviewed, matched against purchase orders and approved by different stakeholders. The objective is to streamline this process by automatically validating invoice data, identifying exceptions and routing approvals when necessary. The agent-aspect comes in for providing recommendations for the approver on what to look for at invoices.