Unlock the Power of Big Data with Enterprise Analytics

Over time, data has assumed a critical role in the world of technology. With increasing digitization, data is no less than a chest of treasure. The value of data has increased to the extent that now it is linked to the value of globally standardized assets like gold, oil, etc. The rise of Big data is the reason behind the unprecedented and massive increment in the value of data.

Gartner defines “Big Data as information assets with a high volume, high-velocity, and a great variety. For enhanced and improved decision-making, it demands cost-effective and highly innovative forms of information processing.”

The origination of the concept of Big Data can be traced back to the 1990s. It is when the organizations acknowledged their ability to generate comprehensive insights about almost everything, that is from a new business opportunity to consumer behavior along with their buying patterns. But it has been recently discovered that unfiltered Big Data is equivalent to unprocessed crude oil or for that matter, raw gold, which means that it is open to exploitation and has massive potential, but after refining. This is where analytics has a major role to play.

We will discuss the concept of Enterprise Analytics, its importance, use, etc. in detail here.

What is Enterprise Analytics?

The analytical processes that an organization collectively applies to enormous data sets to extract meaningful insights are defined as Enterprise Analytics. Also, to drive actions and business strategies, various components are used. These components comprise data, analysis, and exploratory and predictive modeling.

The success of enterprise analytics depends on applying the concoction of certain techniques of data engineering, data management, strategy development, and the use of analytics techniques ranging from simulation and forecasting to optimization and linear programming.

According to a survey conducted by MicroStrategy, for 94 percent of companies throughout the globe, data analytics is an inevitable part of business growth and aids digital transformation strategies. Also, the survey found out that with the rolling of analytics, companies usually report benefits such as enhanced efficiency, quicker decision-making, improved financial performance, and improved ability to identify new revenue sources.

There are four major types of Data Analytics, these are:

• Descriptive Analytics
• Diagnostic Analytics
• Predictive Analytics
• Prescriptive Analytics

1. Descriptive Analytics

This type of Analytics gives an insight into the things that are happening currently or have already happened. The techniques commonly used in this type of analytics include business intelligence and data visualizations.

2. Diagnostic Analytics

Diagnostic Analytics provides context for an event that has happened and is in progress, including why and how. A few standard techniques used in this analytics include data mining, drill-down, data discovery, correlations, etc.

3. Predictive Analytics

This kind of analytics is generally involved in predicting the occurrence of events. Based on historical data, it identifies the occurrence of events. The most common techniques for predictive analytics involve forecasting, regression analysis, predictive modeling, statistical modeling, etc.

4. Prescriptive Analysis

For achieving the desired outcomes, this technique focuses on recommending different courses of action. The standard techniques used include graph analysis, simulation, heuristics, neural networks, machine learning, etc.

Benefits of Enterprise Analytics

There are a plethora of benefits that are offered by Enterprise Analytics. A few are listed below:

Value can be derived from massive amounts of data.

According to the estimates, By 2025, 463 exabytes of data would be generated worldwide every day, which is equivalent to 1 billion gigabytes.

Enormous amounts of data would be generated, even if a single business can collect a small fraction of the data. This much data can make it challenging to examine valuable data, let alone anything meaningful.

The enterprise analytics platforms automate much of the data analytics process; thus, the findings can be presented in a more legible format like a statistical model or data visualization. Enterprise analytics solutions make it easier to access the data insights and more straightforward to understand.

Prediction of outcomes helps in strategization.

Businesses can have a glimpse of the future with the use of predictive and prescriptive analytics, along with receiving the much-needed and targeted recommendations on achieving desired outcomes. Organizations can make well-informed and strategic decisions with the help of this information.

Get a clear idea of the goals and objectives.

Enterprise analytics is not only useful for defining the goals and objectives, but it also aids their achievement. An organization can get a clear idea of the tasks that need to be performed for making a profit and growing the market share by performing an analysis of the industry trends, historical data, industry needs, and competitor data. In addition, organizations can make use of diagnostic analytics for reviewing the past performance and thus identifying weaknesses. Prescriptive analytics can be helpful in generating data-driven recommendations about improvement.

Easy anticipation of consumer needs.

Reviewing customer data is the best way for the company to understand consumers' needs. A clear picture can be gained into identifying the target audience, the problems they face, and what is most important to them using enterprise analytics. Businesses can categorize their consumer base by demographic as well. It makes businesses more accustomed to their customer's needs and enables them to customize and tailor each consumer interaction accordingly.

Maximization of sales along with the marketing spend.

Enterprise Analytics makes it possible for businesses to enhance their sales and marketing spending by making direct contact with consumer choices and preferences.

Businesses can create detailed consumer profiles that contain everything from personal choices to significant life milestones using specific software, like a consumer relationship management solution.

Based on this information, the company's marketing team can devise more targeted campaigns, thus enabling the sales team to determine cross-selling and upselling opportunities. It would also help them in delivering personalized product recommendations.

Risk Mitigation.

Predictive analytics models come in handy to prevent direct exposure to the risk or its mitigation. The enterprise analytics platforms allow you to store all of your data in a centralized location, thus escaping the potential risk of the movement of data back and forth and from one system to another.

Optimization of product development.

With the help of enterprise Analytics, the guessing game for new product ideas and improvements that would appease the customer can be avoided.

One can quickly evaluate the customer opinions, social sentiment, preferences, and more with the help of these enterprise data analytics platforms.

These solutions can also examine whether an R&D project is likely to be completed on budget and on time, thus enabling organizations to shuffle resources for keeping things within the ambit and effectively plan for future R&D initiatives.

Share real-time results.

Real-time reporting is offered by most enterprise data analytics solutions allowing the business leadership to gain essential and current insights, thus sharing throughout the organization. It ensures timely updation of everyone about the business events and enables collaboration between otherwise aloof departments and teams and breaking down silos in the process.

What is Enterprise Data Strategy & Why Do You Need One?

An enterprise data strategy is an organization’s long-term detailed plan for implementing enterprise data analytics at every level of business.

Any organization needs to have a strategy for harnessing the potential of Big Data.

Conclusion

Enterprise Analytics is the need of the hour to make the best use of Big Data in today’s world. It can aid highly effective decisions for the organizations and increase revenue and efficiency.