Why data is essential
“Every company has big data in its future, and every company will eventually be in the data business.”– Thomas H. Davenport, Fellow of the MIT Initiative on the Digital Economy, Co-founder of the International Institute for Analytics, and a Senior Advisor to Deloitte Analytics.
Big data. The term is suddenly everywhere. More than a mere buzzword, big data helps us make sense of the wealth of information around us in ways that can be quantified and compared. Big data predicts and molds business trends, meaning it’s worth a look for investors on the lookout for disruptive potential.
Data has always been at the forefront of business decisions. Enormous recent growth in the volume of data has led to a complete shift in how it can now be used. To keep up with the data revolution, companies must acquire new technology and tools to process mass information more quickly and accurately than ever before. Big data stocks reflect these changes and the growth potential they embody.
By analyzing big data, companies are able to become more agile and solve business problems faster. An accurate understanding of data insights can lead to increased business opportunities and more profitable decisions. Big data analytics are used to study historical trends, make predictions, and assess risks.
What’s more, every person leaves a digital footprint through media, messaging, and device usage. Any time an individual interacts with an automated device, such as a computer or smartphone, a myriad of data points is created by those interactions. Posting, clicking, liking, and messaging combine to form a more thorough picture of the technology user and refining specific, personalized data.
The challenge of handling large data sets
“Big data is at the foundation of all of the megatrends that are happening today, from social to mobile to the cloud to gaming.”– Chris Lynch, Vertica Systems
Big data deals with immense, complex data sets that are too large to analyze using classical approaches. Yet utilizing this data can yield relevant insights and address business needs. Businesses are flooded with ever-increasing quantities of data and their strategic decisions are driven by their ability to analyze it efficiently. However, data has proven impossible to manage using traditional processing approaches.
What prevents effective data use?
Until recently, the potential of big data could not be fully harnessed due to the following critical challenges:
- Data stems from diverse sources and it was impossible to organize these varied sources on a large scale. Useful insights and correlations depend on some form of standardization. For example, it was impossible to extract meaningful results and make comparisons between medical records that are stored differently among different hospitals.
- Organizations and institutions wishing to work with big data don’t typically possess the technological capacity and processing power they would need to analyze it.
- Classical algorithms, tools, and approaches were insufficient to analyze the new paradigm of complex data.
The first and third of these challenges are addressed by AI (artificial intelligence), and ML (machine learning). AI allows businesses to collect, sort, and unify diverse data. Data that seemed disjointed and unmanageable can yield unprecedented correlations using AI. ML then takes the data sets that were compiled and standardized using AI and develops algorithms that allow the data to be utilized most effectively.
The second of the challenges above is addressed by cloud computing. By relocating how data is stored and processed, cloud computing has enabled more and more companies to make use of big data by enhancing security, speed, and cost-efficiency.
An untapped resource
Data levels in 2020 surpassed expectations, likely due to the Covid-19 pandemic. Covid-19 increasingly moved interactions between people into the digital sphere, which yielded greater amounts of data than anticipated.
However, most data produced does not get stored for long term use. A mere 2% of data from 2020 made it into 2021*, pointing to significant unutilized potential for growth in the realm of data storage.
As shown in the graph above, the past decade points to enormous growth for big data companies, which is expected to continue at an annual rate of approximately 25% over at least the next five years. Big data companies’ stocks allow for investment in this rapidly developing field and the savvy investor may seek exposure in their portfolio to big data stocks.
Join the data revolution
Key industries such as healthcare, retail, banking, and insurance, and more are already utilizing big data. A myriad of companies in these and other industries demand solutions that will allow them to capitalize on their data. The ability to store, process, analyze, and standardize data has become more important than ever. In order to not be left behind, promoting the capacity of companies to handle their data is a must.
Investors wishing to benefit from this potential growth could consider companies involved in database management, data platforms, dev-ops, big data analytics, and application programming interface management.
Big data has tremendous growth potential, but there’s no way to know who will emerge as a key player in this ever-developing industry. Therefore, a diversified portfolio is key. Big data stocks should ideally draw from a range of different companies and sectors, making it more likely that investments will yield positive returns.
Big data is rapidly becoming increasingly relevant in almost all industries, touching on every aspect of our lives. In the dynamic market of big data stocks, there is scope for growth that’s worth a look.
* “Amount of data created, consumed, and stored 2010 – 2025,” published by Arne Holst, Jun 7, 2021. https://www.statista.com/statistics/871513/worldwide-data-created/