big-dataThe Big Data space is heating up – to the point that many pundits already see it as the over-hyped heir to “cloud.” The hype may be a bit much, but Big Data is already living up to its potential, transforming entire business lines, such as marketing, pharmaceutical research, and cyber-security. With more than 2.5 quintillion bytes of data being generated daily. It is more than safe to assume that Big Data is gearing up for changing the way we think!

The global big data market reached $208 billion in 2020 and is projected for a steady compound annual growth rate of 10%, reaching $450 billion by 2026, according to Expert Market Research. Here are top Big data companies with potential to grow to grow  in 2022

1. Sumo Logic

What they do: Apply machine learning to data center operations, using data analysis to pinpoint anomalies, predict and uncover potentially disruptive events, and identify vulnerabilities.

Sumo Logic’s Anomaly Detection attempts to solve this pain point by enabling enterprises to automatically detect events in streams of machine data, generating previously undiscoverable insights within a company’s entire IT and security infrastructure and allowing remediation before an issue impacts key business services.

2. Ayasdi

What they do: Apply Big Data analysis in order to solve complex problems, including finding cures for cancers and other diseases, exploring new energy sources, and preventing terrorism and financial fraud.

Ayasdi believes a better approach is to look at the “shape” of the data. Ayasdi argues that large data sets have a distinct shape, or topology, and that shape has significant meaning. Ayasdi claims to help companies determine that shape in minutes so they can automatically discover insights from their data without ever having to ask questions, formulate queries, or write code.

3. Feedzai

What they do: Feedzai uses real-time, machined-based learning to help companies prevent fraud.

It’s no great revelation that online fraud is a major problem. However, its impact is often underestimated. For instance, the Target breach could end up costing as much as $680 million, according to the Ponemon Institute.

Feedzai claims that it can detect fraud in any commerce transaction, whether the credit card is present or not, in real-time. Feedzai combines artificial intelligence (AI) to build more robust predictive models and analyze consumer behavior in a way that mitigates risk, protects consumers and companies from fraud, and preserves consumer trust.

4. CloudPhysics

CloudPhysics goal is to analyze the world’s IT data knowledge and use the information to transform computing, driving out machine and human costs in ways never before possible. Today, their servers receive a daily stream of 100+ billion samples of configuration, performance, failure, and event data from their global user base.

CloudPhysics’ service combines Big Data analytics with data center simulation and resource management techniques. CloudPhysics argues that this approach uncovers hidden complexities in the infrastructure, discovers inefficiencies and risks that drain and endanger resources, and enables what-if analyses that can inform every data center decision.

5. BloomReach

BloomReach Organic Search combines web-wide intelligence and site-level content knowledge with machine learning and natural language processing to predict demand and dynamically adapt pages to match consumer behavior and intent. This helps companies capture up to 60 percent of net-new users. BloomReach also takes a data-driven approach to m-commerce, more accurately matching consumers with content and products. This increases revenue-per-site-visit by up to 40 percent, and drives sales across all shopping channels.

6. Altiscale

Altiscale service is intended to abstract the complexity of Hadoop. Altiscale’s engineers set up, run, and manage Hadoop environments for their customers, allowing customers to focus on their data and applications. When customers’ needs change, services are scaled to fit – one of the core advantages of a cloud-based service.

7. Pursway

Pursway’s software is intended to improve customer acquisition, cross-selling opportunities, and retention. By imprinting a social graph onto existing customer and prospect data, identifying actual relationships between buyers, and identifying target customers who have a demonstrated influence over others’ purchasing decisions, Pursway argues that it can help consumer-facing organizations close the gap between how businesses market and how people actually buy.

8. PlaceIQ

PlaceIQ says that it “provides a multidimensional depiction of consumers across location and time.” This allows brands to define audiences and intelligently communicate with those audiences to support greater ROI. PlaceIQ’s product, Audiences Now, focuses on targeting customers where they are, in real time, creating an immediacy to a brand’s marketing strategy.

9. MemSQL

Big Data and real-time analytics have the potential to profoundly impact the way organizations operate and how they engage with customers. However, there are challenges that prevent companies from fully extracting value from their data. Legacy database technologies are prone to latency, require complex and expensive architectures, and rely on slow disk-based technology.

10. Couchbase

Couchbase is placing its bet on NoSQL. The startup argues that its NoSQL document-oriented database technology provides the scalability and flexible data modeling needed for Big Data-scale projects. Couchbase also claims to offer the first NoSQL database for mobile devices. Via

[Updated 6 Jan 2022]


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