Big data has taken the business world by storm. It has successfully carried away the revolutionary task to capture and process massive data, employ analytics, and gaining actionable insights from the big data. This not only harnessed business potential but also challenged businesses to escape stagnancy. Big data analytics has been the nucleus sight for more than a while and managed to exist as the next big career move for any organization adopting it.
What is Big Data Analytics?
As the word claims ‘Big data’, refers to a huge volume of data or data sets that combine structured and unstructured data received from multiple sources. This type of data is so vague that it cannot be processed by traditional data processing. To make it easier to understand let’s go through the 3 Vs. of big data.
3 Vs. of Big Data
1. Variety: Data varies from one dataset to another dataset. It’s not accessible for the big data to fit in one single data set. A fair example of such data is emails, which are non-repetitive in every manner (in terms of time, destination, attachments, and more). They are uneven and require big data tools to classify them precisely.
2. Volume: Big data companies consume gigantic data as they use AI to do so. The volume of data we come across in our daily lives accounts Ola, Uber, or the lump of data we scroll on social media handles.
3. Velocity: This term elaborates on the tendency of how quickly the data arrives. For example, Facebook’s data has to be processed timely to avoid any errors. As we know, “With great power comes greater responsibility”, and so does with the colossal amount of data comes the urge for velocity.
Big data examines data in a manner which digs out information such as market trends, consumer preferences, hidden patterns, and correlations. This analytics helps in forecasting favorable operations, hike in revenue rates, and happy clients.
Benefits of Big Data Analytics
Every sector is benefitted from big data. Few of them at your glimpse,
1. Sales and Marketing: Evaluating data create opportunities inside and out of the company. Boosting the sales cycle has been one of the most proven benefits of big data. By implementing destination thinking, Natural Language Mining, Artificial Intelligence, and Machine Learning one can speed up their business goals. Big data interprets customer interests and assists the sales and marketing team to make appropriate purchasing decisions.
2. Building good relations: No doubt customer relations are strengthened due to big data. As data observe customer preferences it makes them feel valued and seen. Personalization from big data’s side enables improved customer relationships. This is where Big Data Marketing comes into the picture. Big data marketing is a micro marketing process that processes consumption patterns as well as customer information to offer what they want at the right time.
3. Logistics: Time is the most primitive factor behind distribution and logistics. To measure various factors of transportation, a huge lump of data needs to be processed. For this, planning transportation in consideration of time, minimization of downtimes, maintenance costs, and fluctuation of routes is managed by big data.
4. B2B business: B2B companies rely heavily on big data to gain a competitive advantage over opponents. Does marketing campaign personalization give deeper insights into the fact that whom to target? When to target? And why target?
B2B companies operate gobs of data which is nearly impossible to manage manually. Big data not only offers accuracy but also speeds up the process. A few examples of B2B big data analytics are website traffic data, device data, third-party data, transaction logs, consumer sentiments, press releases, marketing research, product data, and social media posts.
5. Healthcare: Complex data in healthcare is effortlessly managed by Big Data analytics. For example, patient data from the last visit can be recorded and read at the time of need. Also, analyzing DNA structures and developing group-specific drugs is a task, but Big data simplifies it. Classification is the main element in healthcare to which big data is a pillar.
6. Research: Evaluating the data assembled for research is way more complex than a guess. Such types of convolutions are tackled by big data single-handedly. For example, at the Geneva research center, CERN developed 40 terabytes of data per second during an ongoing experiment. This is the impact of data on the science and research sector.
Do you know?
Hadoop data analytics is an open-source method of data analytics that can process and store large amounts of datasets ranging from gigabytes to petabytes. The source clusters several computers instead of one single computer. Including multiple computers enable the flexibility to analyze immeasurable datasets in a fraction of time.
The bottom line of the extract,
Many businesses are still in the process of trying to figure out the value of big data. Those that can recognize the value early on and adapt to the changes will have a much greater advantage against their competitors. Those that are still trying to catch up with this trend will likely find themselves at a disadvantage. While advancement in technology has spiked up the relevancy and need for big data. It has evolved into the most integral component of the foundation of any business. Possibilities with big data are limitless, making it the biggest thing in the future.