Companies Cracking the Data Code


Data can reveal details about consumer behaviour, indicating trends and provide other decision-making insights. So who can help you to navigate this maze of data? We got you covered  – here is a list of innovative companies in the Data Science space.

From healthcare and manufacturing to retail and finance, companies across sectors have begun to recognise the need for data-driven decisions and business operations. As decisions are based on data collected, the demand for data science has soared. 

Assessing animal health, anticipating dangers on construction sites, predicting weather down to the city block, innovative companies in data science are doing all this and more. Here’s a list of Ten innovative data science companies.  

1. Strava

Strava is the leading platform for athletes and the world’s biggest sports community with over 68 million athletes – that allows runners, cyclists and athletes to upload and share workout statistics and routes with each other. Strava has the world’s largest anonymous, aggregated and active transportation data set, which helps city governments and urban planners to discover the most popular bike and walking routes without coding or analytics. It launched Strava Metro in 2020.

With most people now working from home due to the pandemic and a related public concern about taking public transportation, daily travel methods and destinations have shifted massively. Millions of people upload their bike rides, runs and walk to Strava every week via their smartphone or GPS device, and Strava Metro aggregates and de-identifies this data. Making it available to help transportation and city planning groups departments understand changing commute patterns, improve safety, and evaluate infrastructure projects.

Strava also rolled out new premium subscription services to help its 50 million users achieve more tailored goals like reaching a training milestone, analysing specific health data or staying safe by sharing their real-time location with a selected group of people.

2. Aclima

Air pollution and greenhouse gas emissions have become a massive issue globally and can vary wildly, even on a block-by-block basis. Aclima’s sensors and cloud-based platform turn big data about air quality into hyperlocal insights that help governments, advocacy groups and other stakeholders to identify hot spots so they can take action. 

Aclima translates measurements from its net seamlessly into meaningful insights for the public through a free online app, currently being piloted by environmental justice communities. Search air pollution levels by address to understand conditions where you live, work, play, and learn. Collaborate to reduce emissions and protect public health. In 2019, the company began mapping and analysing air quality across the 101 municipalities in the Bay Area in the US — the first pan-region research project of its kind. 

3. Wattpad

Wattpad – the world’s most-loved social storytelling platform, hosts stories from 4 million self-published readers and uses machine learning to help its 90 million monthly readers find something that suits their tastes. Wattpad uses the data from its vast catalogues to identify which stories might be most successful as physical books. Its Wattpad Books imprint has published tales like teen drama and the Afrofuturist romance. Its data ambitions are not limited to finding hits in print, it’s also going after the big screen with Wattpad Studios, which produced After (one of 2019’s highest-grossing indie films).

4. Snowflake

Snowflake can call on its tools for storing, analysing and acquiring data to tackle practically any business challenge. This point was never more clear than in 2020 when its customers used its platform to do everything from forecasting hospitalisation rates during the Covid-19 pandemic to scaling up meal delivery services as in-restaurant dining became quite impossible. In September 2020, Wall Street rewarded the company by giving it the biggest IPO in software history.

5. (earlier ClimaCell) – the world’s only weather intelligence platform, aims to change the way cities think about weather by predicting temperature, precipitation, humidity, visibility and lightning strikes for areas as small as a city block. Its micro-weather forecasting product, called HyperCast, combines data from cell towers, street cameras, connected vehicles and IoT devices with NOAA radar data to get weather predictions that are far more accurate than other forecasting services offer.  

In 2018, the company’ snowfall models were piloted by multiple North American cities, and few Indian municipalities are testing its flood alert system. It is also used by airlines like Delta and JetBlue, stadiums, trucking and construction companies.

Also Read: The AI Arms Race

6. LeapAnalysis

LeapAnalysis is the world’s first virtualised semantic search and analytics engine that combines semantic technology with machine learning to seamlessly access and analyse all your data. Its cloud virtualisation technology allows companies to work with data right where it already is, so no data aggregation is required. This dramatically reduces analysis efforts in areas such as drug discovery, disaster management and analytics. For one of LeapAnalysis’ customers in the pharmaceutical industry, avoiding the need to move data around slashed the time it took to conduct a research project from 11 days to 3 minutes.  

7. Moda Operandi

Moda Operandi provides access to hot designer looks through its online marketplace of luxury fashion, accessories and home decor. The startup started to use data about which items were most popular in its online Trunk shows, where shoppers can preorder the latest fashion trends they have seen on the runway for a limited time. Moda Operandi found that popular Trunk Show items tend to sell 10 times more on the company’s app than less coveted items. From the time it started using Trunk show data to inform inventory, the company has increased the sell-through rate on those items by 100 per cent. In 2020 the company raised $100 million in funding. 

8. Autodesk

The manufacturing software giant Autodesk launched Construction IQ — a software program that can predict risks and dangers in construction projects. By analysing data such as observations, checklists, subcontractors assignments, and historical data from across Autodesk’s construction management platform, Construction IQ can detect where a fatal injury might occur or where a contractor may be wasting materials. The algorithm was trained using more than 150 million data points gleaned from nearly 30,000 real projects. The company says that now 200 general contractors are using Construction IQ to make their projects safer and more efficient. 

Also Read: Digital Transformation’s Impact on Industries: Microsoft Report 

9. Kinsa

When the COVID-19 pandemic struck, checking people’s temperature became a critical tool for identifying their health status. Rather than simply performing that task for individuals, Kinsa’s smart thermometers power its AI-based US HealthWeather map, which helps doctors and scientists identify COVID-19 hotspots early on. In 2020, five states and ten cities in the US worked with the company to distribute a half-million smart thermometers in areas at a disproportionate risk. 

10. Duality Technologies

Even if we have privacy issues, data collection is always gonna be increasing. Duality Technologies promises a new way of analysing data while it is still encrypted – completely preserving the privacy and security of a data set while also helping businesses learn from its patterns. The company’s SecurePlus platform – launched in fall 2019, uses a technique called homomorphic encryption, which was earlier just a theory until Shafi Goldwasser – an MIT cryptography expert and Turing Prize winner put it into use. She is one of the co-founders who is poised to create a new gold standard for data analytics to keep data private while still allowing businesses to glean insights from the maze of data.