How to Extract Data in Google Sheets & Excel Fast - Guide

Every growing business eventually discovers the same painful truth: the bottleneck isn’t data collection, it’s data extraction. Your team drowns in Google Sheets and Excel files, exporting, filtering, and copying the same slices of information over and over.In this guide, you’ll see practical ways to extract data in Excel and Google Sheets – from classic, manual techniques to no‑code automation and finally AI agents that handle the grunt work for you.## 1. Traditional, Manual Ways (Great for Getting Started)### 1.1 Filters and Filter Views**Excel:**1. Select your data range (including headers).2. Go to **Data > Filter**.3. Click the dropdown in a header (for example, "Status").4. Check or uncheck values, or use **Number Filters** / **Text Filters** to set criteria.5. Copy the filtered rows to a new sheet if you need a permanent extracted table.Docs: https://support.microsoft.com/en-us/office/filter-data-in-a-range-or-table-2fbb0078-02df-4f95-9d9a-5ee3b8b8578f**Google Sheets:**1. Select your range.2. Click **Data > Create a filter**.3. Use the filter icons in headers to select criteria.4. For reusable setups, use **Data > Filter views** and save named views.Docs: https://support.google.com/docs/answer/3540681**Pros:** Simple, visual, no formulas. **Cons:** Repetitive; easy to make mistakes when criteria change often.### 1.2 Text to Columns / Split Text to ColumnsIf you import CSV data where several fields are jammed into one column, split them first.**Excel:**1. Select the column with combined text.2. Go to **Data > Text to Columns**.3. Choose **Delimited**, click **Next**.4. Select delimiters (comma, semicolon, space, etc.).5. Choose a destination cell (or overwrite the original) and click **Finish**.Docs: https://support.microsoft.com/en-us/office/split-text-into-different-columns-with-the-convert-text-to-columns-wizard-30b14928-5550-41f5-97ca-7a3e9c363ed7**Google Sheets:**1. Select the column.2. Click **Data > Split text to columns**.3. Choose the separator (comma, space, custom, etc.).Docs: https://support.google.com/docs/answer/6325535**Pros:** Cleans raw imports so you can filter/join later. **Cons:** One‑off; if the source file changes, you repeat the steps.### 1.3 Lookup Functions (VLOOKUP, INDEX/MATCH)When your data is spread across multiple tables, lookup functions extract matching values.**Excel VLOOKUP example:**1. Assume **A2:C100** is your table (Name, Dept, Age) and **E2** has the name you’re searching.2. In **F2**, type: `=VLOOKUP(E2, A2:C100, 3, FALSE)`.3. Copy the formula down.Docs: https://support.microsoft.com/en-us/office/use-excel-built-in-functions-to-find-data-in-a-table-or-a-range-of-cells-6777ec9b-6191-426a-8d45-196ecbf2a186**INDEX/MATCH pattern (more flexible):**`=INDEX(C2:C100, MATCH(E2, A2:A100, 0))`**Google Sheets:** Functions behave similarly: `VLOOKUP`, `INDEX`, `MATCH`.Docs (Sheets VLOOKUP): https://support.google.com/docs/answer/3093318**Pros:** Great for building slim, extracted reference tables. **Cons:** Formulas can become brittle; complex workbooks are hard to maintain.### 1.4 The FILTER Function**Excel 365+ and Google Sheets** both have `FILTER`, which is almost purpose‑built for extraction.**Excel:**1. On a new sheet, in **A2**, type something like: `=FILTER(Master!A2:J100, Master!G2:G100="COLD")` (wrap COLD in quotes in Excel).2. All rows where the "Station" column equals COLD spill into the new sheet.**Google Sheets:**`=FILTER(Master!A2:J, Master!G2:G = "COLD")`Docs (Excel FILTER): https://support.microsoft.com/en-us/office/filter-function-f4f7cb66-82eb-4767-8f7c-4877ad80c759 Docs (Sheets FILTER): https://support.google.com/docs/answer/3540681#filter**Pros:** Dynamic; updates automatically when the master table changes. **Cons:** Criteria live in formulas, which non‑technical teammates may fear editing.## 2. No‑Code Automation MethodsManual steps are fine for ad‑hoc analysis. For recurring work – weekly sales reports, campaign pulls, cohort exports – you want automations that reset themselves.### 2.1 Power Query in ExcelPower Query (Get & Transform Data) is a point‑and‑click way to define repeatable extraction and cleaning steps.1. In Excel, go to **Data > Get Data** and choose your source (Workbook, CSV, database, etc.).2. In the Power Query Editor, use **Filter Rows**, **Remove Columns**, **Split Column**, and **Group By** to shape the data.3. Click **Close & Load** to load the result into a new sheet or data model.4. Next time, just click **Data > Refresh All** – your extraction pipeline reruns automatically.Docs: https://support.microsoft.com/en-us/excel/power-query-3f7a0b4e-3f3a-4e6c-9c7f-34a3b9e7b0b9**Pros:** Very powerful, no coding, ideal for repeated jobs. **Cons:** Desktop‑centric, learning curve for non‑analysts.### 2.2 Google Sheets QUERY Function`QUERY` lets you write SQL‑like statements over a range – an incredibly compact way to extract slices.Example: pull all leads from the US with spend over 1000:`=QUERY(A1:F1000, "select * where C = 'US' and F > 1000", 1)`Steps:1. Put raw data on a "Data" sheet.2. On a "Report" sheet, insert a `QUERY` formula pointing to the data range.3. Adjust the SQL‑like string to filter, group, or aggregate as needed.Docs: https://support.google.com/docs/answer/3093343**Pros:** Very compact, auto‑updating, powerful for analysts. **Cons:** Requires SQL‑style thinking; errors can be cryptic.### 2.3 iPaaS Tools (Zapier, Make, etc.)You can also set up no‑code workflows that move and extract data into Excel or Google Sheets.Common patterns:- **CRM → Google Sheets:** When a new deal is created, append a filtered row into a "Pipeline" sheet.- **Form tool → Excel Online:** On new form submit, add a row to a specific table if certain answers match your criteria.Typical steps:1. Choose a trigger app (e.g., HubSpot, Typeform).2. Add a filter step (e.g., only if `deal_amount > 10000`).3. Add an action: **Create Row in Google Sheets** or **Add Row into Table in Excel Online (Business)**.**Pros:** Hands‑off once configured; connects many SaaS tools. **Cons:** Limited to what connectors expose; complex logic can become a maze of steps.## 3. At‑Scale Extraction with AI AgentsWhen you’re running dozens of sheets and workbooks across desktop, browser, and cloud, even no‑code tools hit limits. This is where AI computer agents, like those powered by Simular Pro, become your virtual data ops team.### 3.1 Desktop Workflow Agent for ExcelImagine a Simular AI agent that:- Opens your master Excel workbook on your Mac.- Runs Power Query refreshes.- Applies FILTER or Advanced Filter across multiple sheets.- Copies the resulting tables into new "COLD", "HOT", or "Enterprise" workbooks.- Saves them to the right folder or uploads to SharePoint.**How to implement at a high level:**1. Record the exact human workflow once: which file, which sheets, which filters.2. In Simular Pro, configure an agent to reproduce those mouse and keyboard actions.3. Set up a webhook or scheduled trigger so the agent runs every morning.**Pros:**- Works with legacy Excel files, desktop apps, and logins.- Handles multi‑step, cross‑app workflows (e.g., download CSV from a portal, clean in Excel, upload somewhere else).**Cons:**- Requires initial onboarding: you must demonstrate the workflow clearly.### 3.2 Cross‑App Agent for Google Sheets + Web ToolsA Simular agent can:- Log into your ad platforms.- Export performance CSVs.- Open Google Sheets in the browser.- Use built‑in features like **Split text to columns** and **QUERY**.- Paste clean extractions into reporting sheets for your team.Because Simular’s execution is transparent and every action is inspectable, a non‑technical ops lead can open the agent’s run history and see exactly how data was filtered and extracted.**Pros:**- Replaces a human spending hours in the browser.- Easy to audit; you see every click and formula.**Cons:**- You still need a clear specification of the slice you want (criteria, ranges, sheet names).### 3.3 Omnichannel Extraction PipelinesAt scale, you can chain agents:- Agent A: Scrape or download data from websites and APIs into a staging sheet.- Agent B: Clean, split, and deduplicate via Excel/Sheets.- Agent C: Push curated extracts into your CRM, BI tool, or finance system.Because Simular focuses on production‑grade reliability (thousands to millions of steps) and offers webhook integration, these AI agents can sit inside your existing pipelines, quietly doing the grinding spreadsheet work your team hates.The outcome: data extraction in Google Sheets and Excel stops being a fragile, manual chore and becomes a dependable, automated capability you can build the rest of your growth stack on.