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6 Big Data Tools for Startups

If you thought big data was only for big businesses, think again. Small businesses jumping on the trend will be largely responsible for doubling the share of total data collected by companies between 2015 and 2025.

Behind startups’ increased interest in data collection is a suite of new tools. Whereas AI and data visualization tools were once mostly confined to the enterprise, smaller firms are now betting a big chunk of their tech budget on analytics software.

Which big data tools are tipping the scales for startups? The following can help your company collect, prepare, and analyze more data than ever before:

1. Amazon Web Services

AWS is a platform-as-a-service and infrastructure-as-a-service provider that works with a huge range of applications and data. AWS stores, hosts, and crunches data for millions of organizations around the world, which keeps costs low. Its 69 data centers span 22 regions around the world, ensuring that analyses run quickly and that your data can’t be lost. Plus, it runs on a pay-as-you-go pricing model, which is ideal for startups in need of financial flexibility.

2. ETLrobot

Although AWS can host almost any type of data, actually making use of it requires you to consolidate it into a single format and storage location. ETLrobot is a data-pipeline-as-a-service tool, meaning that it will extract, transform, and load your data into your designated warehouse. A no-code tool, ETLrobot offers a variety of integrations. In addition to hooking up with analytics systems, it works with CRM platforms, payment gateways, and developer tools so you can analyze many different types of data. 

3. Tranzlogic

Tranzlogic promises to turn transactions into insights, leveling the payment analytics playing field for small companies. Tranzlogic enriches credit card transactions with valuable customer and market insights, including geographic, demographic, economic, and psychographic attributes.

Information about who your customers are and what they stand for has broad business value. Use it to make your marketing more relevant, spot new market segments, and improve your customer experience.

4. Google Analytics

Especially if your company relies on the G-Suite, Google Analytics is a great tool for getting a deeper understanding of your customers, your website’s performance, and your inbound traffic.

Google Analytics straddles the analysis and reporting spaces, and it’s built to work with Google’s other advertising and publishing services. Although it’s free for anyone with a Google account to use, the paid version — Google Analytics 360 — is worth the investment. Google Analytics 360’s additional capabilities include advanced analytics, Google’s BigQuery data export feature, data-driven attribution for cross-platform customer journeys, and more. 

5. Kissmetrics

Kissmetrics’ landing page says what startup leaders need to hear about big data: Advanced product analytics shouldn’t break the bank. Kissmetrics covers a lot of ground, including:

  • Which search terms bring the most revenue for your business.
  • How frequently customers are leaving and who they are.
  • Attributes your converting customers have in common.
  • Which digital product features people are — and aren’t — using.

Although those details have value for sales and product development, Kissmetrics’ platform is decidedly focused on marketing. It includes customer journey reporting, cohort analysis, behavioral predictions, and trigger-based notifications. 

6. Tableau

For small business leaders who are searching for the story in their data, Tableau is a great tool. Users can create interactive maps that break down data by geographic region, sales territory, customer demographics, and more. Tableau works with Hadoop, Spark, and NoSQL databases, though its reports are accessible by nontechnical team members. Tableau Prep, a newer part of the platform, takes the stress out of data cleaning, while Tableau Mobile delivers insights on the go.

Big data can’t be mastered with a spreadsheet and a college statistics course. But no longer is an on-staff data scientist required, either. By investing in the right tools, small companies can extract insights that were off-limits to them even a couple of years ago. And in a business environment that’s built on big data, those insights can make a big difference.

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