Best Big Data Tools and Software

What is Big Data Analytics Tools and Why is it Important?

This article will discuss some of the classic examples of big data analytics in business use cases and how it can positively impact day-to-day business operations. For all of us, big data analytics has always been a familiar concept from its beginning, which now brings in a huge digital transformation over the last decade. Unfortunately, however, many businesses fail to make the most out of big data and its positive impacts on businesses of all types.

Last year, a Forrester report showed that about 60% to nearly 75% of all the data procedure across the globe by enterprises goes unused for any type of analytics. However, from marketers to top decision-makers, businesses are largely recognizing the importance of gathering and processing data about all aspects of the business to guide their daily operations and critical decision-making process. We can see the reflection of this in the ERPs, which are now highly in-demand applications in SMBs lately.

• Cost reduction
• Better resource utilization
• Efficient business processes
• Judging the needs of customers
• Focused marketing
• Improvise sales
• Improving the efficiency of machinery
• Better management or retail and supply chain and so on

From the year 2017, at least about 53% of companies worldwide have started leveraging big data in some way or another to make informed decisions, and this number is steadily growing. Developments like RPA (robotic process automation) and AI are helping to fuel this growth in the usage of big data, making it easier to sort through the huge volume of data and process it insightfully.

So, to remain competitive now, analytics should be the backbone of business operations and decision-making. To incorporate big data analytics into your database workflow, you may assist proven professional database management consultants like RemoteDBA. Further, we will discuss how SMBs can leverage big data in business and how big data analytics can impact business processes.

Big Data in Information Technology

It is vital to have a solid IT infrastructure to enhance the efficiency of an organization alongside ensuring security and cost savings. Analytics will support a strong IT infrastructure's deployment and smooth functioning and offer the professionals who manage it the needed tools to stay on top of things. As we can see, IT applications leverage analytics in three distinct ways.

1. Network performance

Analytics can give a proper insight into network performance parameters like speed, traffic, network up and downtime, user activities, and even printing and other connected environments. Using data collected through this monitoring, the admins can understand the traffic movement in the network and tweak processes as needed for better efficiency.

This is done by an analysis engine, which can assess data from various sources such as servers, connected devices, servers, and the flow of traffic. Doing proper network analytics will help the IT teams to spot the bottlenecks in the network early and check for the health of connected devices to fix the issues as they pop up.

From the operations standpoint, network analytics will help automate and compare how a network performs against the desired level. During analysis, your network may also deviate from the routine operations at optimal capacity, which information can be delivered to the IT team to discover what issues cause the slowdown and find remedies.

In other terms, network analytics will let us ensure that all operations are running smoothly, and catching the network performance issues in real time will help eradicate any costly downtime.

2. Cybersecurity

The number of cyberattacks is also increasing. However, analytics can be effectively deployed to learn the behavior of security breaches and predict the possibility of another one. Even though it is difficult to predict the possibility of an attack, according to IDC, big data may be the key to it, which will shed some light on best cybersecurity practices and avoid the chances of any attacks.

Data can also be used to understand whether any unusual activity is happening, which might warrant any alert as a strange login attempt or a strange query to fetch data. This security measure is achieved by analyzing historical and live big data sets with the help of machine learning systems to understand the trends and patterns.

3. Marketing

One of the biggest utilities of big data is marketing. For example, big data analytics help the biggest e-commerce platforms like Amazon and Alibaba, etc., to get information on what their customers are most interested in. The marketing analysts then use this information to strategize their email campaigns and social media reach. You may be getting such promotional emails from these sites recommending you some particular products, which may have amused you by thinking how they know what you exactly need at that point! They have made the right judgment based on your tastes and preferences by analyzing the big data about your online behavior and compiling those through the ERP.

We can see that analytics first had shown its mightiness in marketing. Business enterprises started to uncover ways to entice their customers to take the call to action on their advertising effort through value propositions. Now, big data analytics is a proven strategy for marketing that;

• It helps marketers to get a real sense of different market segments and audiences.
• Offer an in-depth understanding of customer behavior and choices.
• Help experiment with newer products and better approaches for marketing.
• Offer the best strategies to augment user experience
• Make the A/B testing much easier
• Assist in the optimization of the product and service pricing strategies

Conclusion

So, ranging from IT to cybersecurity, marketing to human resources, big data is now turning out to be the backbone of business operations and decision-making companies to make more compelling and informed decisions to drive more productivity and profitability. Advanced big data solutions and tools will enterprises take advantage of their competitors.