Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups working on solutions for industry 4.0. As there is a large number of startups working on a wide variety of solutions, we decided to share our insights with you. This time, we are taking a look at 5 promising Big Data & Analytics Startups.
Heat Map: 5 Top Big Data & Analytics Startups
For our 5 top picks, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 5 interesting examples out of 910 relevant solutions. Depending on your specific needs, your top picks might look entirely different.
Sota Solutions – Predictive Analytics
Predictive analytics is a subcategory of advanced analytics and big data that allows for the prediction of future events and occurrences based on past sets of data. For industry 4.0, it is most commonly used as a predictor of possible machine failures, giving manufacturers a chance to carry out predictive maintenance work to lower the machines’ downtime and potential losses. German startup Sota Solutions uses big data to predict the utilization of various types of industrial machinery, increasing its utilization and making forecasts more accurate. One of their clients, Klingenberg Berlin, operating in large-scale printing saves over 100,000 sheets of paper per year thanks to the ability to analyze past printing data and applying these algorithms in combination with Artificial Intelligence (AI) to fine-tune the machine’s settings.
Prognostic – Prescriptive Analytics
Prescriptive analytics is considered to be the first step when it comes to using big data. It leverages past data and attempts to predict the possible outcomes of certain decisions in order to choose the best possible option. Autonomous vehicles are well-known for using prescriptive analytics to get valuable insights. British startup Prognostic develops solutions that allow for continuous monitoring of data from the Internet of Things (IoT) sensors and devices. These devices measure and control vibration, temperature, noise, and other specifications to detect failure patterns, provide users with real-time insights, optimize supply chains, and monitor fuel and energy use. Their platform enables enterprise-level security, scalability, and integration with existing IoT infrastructure.
Terracotta – In-Memory Analytics
In-memory analytics, also known as streaming analytics, is becoming more and more popular due to its ability to process data in real-time, being captured by IoT devices. In-memory analytics is an approach to shorten query response times to facilitate faster decision making. Currently, querying data resides in a computer’s random access memory (RAM) rather than being stored on physical hard drives. The US-based startup Terracotta develops in-memory data management solutions that enable companies to process large volumes of data to improve application performance at scale.
Wavefront – Cloud-Native Real-Time Monitoring
Continuous monitoring is especially important for a company’s information security as it allows to analyze for real-time gathering of data and processing it. Big data security analytics are able to go through countless data streams and detect relationships between security-related events and potential threats. The US-based startup Wavefront offers a cloud-native, continuous monitoring, and real-time analytics solutions at scale. Their AI Genie automatically finds performance anomalies and capacity bottlenecks allowing for smart problem solving. Their solution also creates automated dashboards and automatically alerts users about information that is relevant for them.
Prevedere – Customer Demand Forecasting
Demand forecasting uses big data and analytics to predict customer demand for certain goods or services, based on how it performs in the market. Many factors such as expert opinion, market research, global market data, and other economic and behavioral data are also considered for forecasting. US-based Prevedere offers its demand planning solution which conducts demand forecasting for various economic indicators based on historical data, current market trends, inputs from the sales team, and real-time economic data to analyze all the stock tickers on NASDAQ for the past 20 years, along with numerous consumer price indices and oil prices.
What About The Other 905 Solutions?
While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence for your Proof of Concept (PoC), partnership, or investment targets. The 5 startups showcased above are promising examples out of 910 we analyzed for this article. To identify the most relevant solutions based on your specific criteria and collaboration strategy, get in touch.