Incorta Leverages PaaS For Market Expansion

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According to a Markets and Markets report, the global big data market is estimated to grow from $138.9 billion in 2020 to $229.4 billion by the year 2025 at a CAGR of 10.6%. San Mateo-based Incorta is counting on a PaaS strategy to make it big in this highly competitive market.

Incorta’s Offerings

Incorta was founded in 2013 by Oracle alumni, Hichem Sellami, Klaus Fabian, Matthew Halliday, and Osama Elkady. The co-founders wanted to set up an organization that would begin developing a Direct Data Mapping engine and platform. While working at Oracle, the founders realized that there was a massive disconnect between the expected value of data and what companies were actually getting out of it. Traditional approaches and architectures were not helping organizations get the best out of their data collected from multiple data sources. They realized that organizations were investing heavily in data warehousing and implementing advanced projects, but very few of these projects were succeeding due to a lack of the right analytical tools. Incorta was set up with a disruptive vision for what the future of data analytics would look like. It focuses on providing solutions for complex data analysis that have challenged data-driven enterprises, thus allowing them to become more agile and competitive.

Incorta leverages its smart data lake to collect the data from multiple sources. It feeds the data to cloud data storage, puts it in a standard format, and then applies machine learning and predictive modeling to incorporate analytics for business users. Organizations are thus able to access data and collaborate around that data in real-time.

Traditional data projects follow the ETL methodology – extract, transform, load. The process takes data out of one database, modifies it to fit into a format compatible with the target database, and then adds it to the target database. The ETL process also includes flattening the data or building a simple model so the data can be utilized by business users. But the ETL process ends up taking a lot more time, and the users end up remaining stuck on using solutions like Excel to conduct analysis. Incorta, instead, strips out the ETL step. It does not require the data to be flattened and can load the data in the same shape that it was originally generated in, thus accelerating the process.

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Disclosure: All investors should make their own assessments based on their own research, informed interpretations and risk appetite. This article expresses my own opinions based on my own ...

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