> ## Content Index > Fetch the complete content index at: https://www.thedigitalspeaker.com/llms.txt > Use this file to discover other available public pages before exploring further. # How Small Data Can Also Be Big Data - URL: https://www.thedigitalspeaker.com/how-small-data-can-also-be-big-data/ - Published: 2013-09-03T00:00:00.000Z - Updated: 2026-08-04T05:34:36.000Z - Description: Small data can become big data by cleverly combining various data sets with various data formats when developing a big data strategy - Author: Dr Mark van Rijmenam, CSP - Tags: Big Data Gartner’s definition of [big data](https://www.thedigitalspeaker.com/big-data-speaker/) dates back from 2001, when Doug Laney the 7 V’s) that are important for organizations to take into account when developing a big datastrategy. However, the original definition of big data suggests that organisations can only develop a big data strategy if they have vast volumes, terabytes or more, of data. IDC even [defines](http://www.idc.com/getdoc.jsp?containerId=prUS23355112&ref=thedigitalspeaker.com) big data projects as projects that contain a minimum of 100 terabyte of collected data. If we take that definition as a starting point it would mean that very few organizations could develop a big data projects as only the biggest (online) corporations collect so much data already today. Looking at Gartner’s Hype Cycle of Emerging Technologies, it would probably take a lot longer then 5-10 years before big data hits the plateau of productivity if we take the definition of 100 Terabytes of data as a starting point. It would for sure mean that Small and Medium Enterprises, and especially the small businesses, could forget about big data. Fortunately, this is not the case and SME’s can also develop a big data strategy. With small data I do not refer to [IBM’s definition](http://www.ibmbigdatahub.com/infographic/taming-big-data-small-data-vs-big-data?ref=thedigitalspeaker.com) of small data. They define small data as low volumes, batch velocities and structured varieties. Small data however can be any form of data, structured and unstructured and in real-time or in batch processing. Small data simply refers to smaller volumes. Gigabytes and a few Terabytes instead of Petabytes or more. It is true that the amount of data we create is growing rapidly, but there are still many organisations that only collect a few Gigabyte of data. Quite often these, smaller, businesses believe that therefore they cannot develop a big data strategy. Personally however, I believe that a big data project does not have to involve vast amounts of data; connecting various (smaller) data sets can give even more insights than analysing one vast big data set. Therefore, as I mentioned earlier, a small business has to look differently at big data. Simply because less data is created, does not mean that they cannot develop a big data strategy. Especially when those smaller company-owned data sets are combined with public and social data sets, great insights can be achieved that can bring a small company forward. In addition, if a company wants to grow their small data sets to become big data sets after all, they should start looking for new data creation opportunities. Data can literally be found everywhere and it is just a matter of collecting it in order to use it. So, small data can become big data by cleverly combining various data sets with different data formats; Combine weather data with your restaurant’s sales data to discover the impact of rain on your items sold and as such adjust your purchasing behaviour. Combine your customer data with their sentiment online to surprise them and create long-lasting relationships. Track how your customers behave through your shop and combine it with your sales data to see how you can adjust and improve your floor plan. Or combine online sales data with offline customer profiles to see how you can optimize your multi-channel approach for your small retail shop. The opportunities are endless and also small data can provide big insights. Image: [RGBStock](http://www.rgbstock.com/photo/mifGnv6/Harddisk?ref=thedigitalspeaker.com) ##### *Image Credit:* [*allstars / Shutterstock*](https://www.shutterstock.com/g/allstars?ref=thedigitalspeaker.com) ## Frequently asked questions ### What is the difference between big data and small data? Big data traditionally refers to vast volumes of data, with definitions like IDC's requiring a minimum of 100 terabytes for a project to qualify. Small data simply means smaller volumes, measured in gigabytes and a few terabytes rather than petabytes. Unlike IBM's definition, which ties small data to low volumes, batch velocities and structured varieties, small data can actually be structured or unstructured and processed in real-time or batch.》 [Link to this question](#faq-what-is-the-difference-between-big-data-and-small-data) ### Can small businesses develop a big data strategy without huge datasets? Yes, small businesses can develop a big data strategy even without massive volumes of data. A big data project does not require vast amounts of information; connecting various smaller data sets can generate even more insights than analysing one huge dataset. Small companies simply need to look at big data differently, since creating less data does not prevent them from building an effective data strategy. [Link to this question](#faq-can-small-businesses-develop-a-big-data-strategy-without) ### How can combining data sets create big insights from small data? Small data sets can produce big insights when combined creatively with other data sources, especially public and social data. Examples include merging weather data with restaurant sales data to see how rain affects purchases, linking customer data with online sentiment to build relationships, tracking in-store customer movement alongside sales data to improve floor plans, and combining online sales with offline customer profiles to optimize multi-channel retail strategies. [Link to this question](#faq-how-can-combining-data-sets-create-big-insights-from-small) ### How can a company turn its small data into big data? A company can grow its small data sets into big data by actively seeking new data creation opportunities, since data can be found almost everywhere and simply needs to be collected and used. By continuously gathering more data and combining various data sets with different formats, a business can expand its data volume over time while still gaining valuable insights along the way. [Link to this question](#faq-how-can-a-company-turn-its-small-data-into-big-data)