As businesses are leaning towards a more technological dependency, the big data race is fiercely contested. Not just huge multinational companies, but small businesses are also churning out data and consuming at an alarming rate. The trend is related to knowledge is power. The simple goal here is: collect lots of data, analyze and process it to generate insights that will give a competitive advantage to the wielder. If the future is truly of Big Data and from this moment it seems like it is, then no organization can afford to be left out while other rivals will have an advantage over them. This is a classic scenario for organizations, where they are scared and excited at the same time.
Companies nowadays are in investment frenzy on data scientists, data warehouses, and data analytics software, though most of them don’t have much to show for. Data as a service model is emerging and organizations are appointing Chief Data Officers to oversee data management.
Large and, publicly available data sets, easier tools, wider distribution of analytical skills, and early stage artificial intelligence software is leading to a burst of economic activity and increased productivity comparable to that of the Internet and PC revolutions. With speed, agility, and innovation determining the winners and losers, Big Data allows us to measure everything quantitatively. Real-time data analysis and pattern recognition are exposing interdependencies and connections that will lead us to see everything differently.
Smarter Analytics, Not Bigger Data
It is no longer enough to get only bigger, but getting smarter is the key to go ahead in the race of Big Data analytics. Yes, the growing choice of off-the-peg integration products has made data collection more accessible, but it is of no use when large data get unused. Oracle, Microsoft, SAP, and IBM have spent more than USD 15 billion combined on buying software firms specializing in data management. Big data is seen by many to be the key that unlocks the door to growth and success.
Although Big Data analysis is an incredible tool to optimize businesses, it has it’s limitations. Data Analysts tease out correlations to find links between variables. But just because two variables are correlated, it does not mean there exists a causative relationship between them. A good consultancy will help you to figure out which correlation will mean something to the business.
Big Data is used to find correlations and insights using an endless array of questions. However, it’s up to the user to figure out which questions are meaningful and need to be answered correctly. Because much of the data that you need lies behind a firewall or on a private cloud, it takes technical expertise to efficiently get this data to an analytics team. Sometimes the tools we use to gather data sets are imprecise. For example, Google tweaks its algorithm of searching ways frequently, which will give results likely to be different than other days. Hence, if Google search is used to generate data sets, then the correlations that are derived will change too. Another very important limitation associated with Big Data analytics is the importance of security. The information that is provided to a third party could get leaked to customers or competitors. Eventually, you need to know how to use big data to your advantage in order for it to be useful.
A Future after Big Data
Believe it or not, the era of Big Data is coming to a close. The lingering death of one of the most overhyped and poorly understood terms, since the phrase “cloud computing,” is evident from the fact that many companies have not been able to outdo their expectations, which were hugely based on analytics of Big Data. The reason behind this could be associated with vendors, providing analytics software and services, industry leaders or more importantly the media who got the ball rolling in the first place.
Any established firm offering a storage or analytics product for a tiny or a large amount of data is now branded as big data, even though their technology is as it was 5 years ago. Big data as a technological category is becoming increasingly meaningless, as every industry leader includes the phrase in their talks and repeat it as many times in their pitches.
As the industry develops, there won’t be any single term replacing the Big Data moniker, though there will be different tools and technologies, narrowly focused and highly specialized than Big Data. Some of these buzzwords that might catch attention in the near future are:
Smart Data– It’s an emerging pattern in Big Data scene involving the productization of incessant data through predictive analysis. It relies on advanced techniques in statistics and machine learning to recognize and exploit patterns. In essence, companies have stopped relying on humans to interpret data, and are looking forward to machine-captured data through predictive analysis.
Data Science– Data science is a new field that utilizes advanced techniques in statistics, machine learning, natural language processing, and computer science to extract meaning from large amounts of data.
Predictive Analytics– Lingering in relative anonymity for many years, Predictive Analytics is coming in their own. Core to both data science and smart data, it involves using historical data to predict future events. So, if you can anticipate the future, you can also change it.
There are a vast number of data analysts, working for consulting agencies, using data mining, modeling, and optimization to gain insights into customer preferences, trends and more.
Companies have come to rely on these services more acutely nowadays. Even with its limitations, Big Data has evolved the way of doing business in every industry. With every company vying for these services to get an edge over their competitors, the trend of Big Data is not fading out soon, especially while the companies are relentlessly investing in it. While this looks all good and well for sales pitches and publicity, in reality, it is projecting an immensely different picture. Companies, more importantly, small businesses, are not meeting their expected turnover even with the help of Big Data analytics, though this may not be true for major organizations.
Not all Eggs in the Same Basket
Understanding what Big Data can do for an organization can be expressed in one word: Knowledge. It equips you with the capacity to make more intelligent decisions, with the competence to streamline and optimize your business, and with the ability to make your employees work better than before. By analyzing the information gathered about your business, employees and customer, you can put yourself ahead in the competition. But this will only work if you know what you are looking for.
Given the success it has had over the last few years, it is no denying that Big Data will be instrumental for any company to succeed. But putting up a caution sign may help companies to tread this path more carefully. Moreover, companies have to start understanding the role of Big Data analytics, if any, in their business strategy and accordingly set up a plan which will lead to success. Besides, companies don’t have to completely depend on Big Data when they have other resources at their disposal.
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