Some of the Emerging Trends in Data Analytics

Business analytics refers to the exploration
of an organization’s data. The exercise emphasizes statistical analysis and is
common among companies that opt for data-driven decision-making. Such
organizations consider their data as assets and actively identify ways for
gaining a competitive edge in their respective industries.

The process’s success largely depends on data
quality and professional data analysts who acknowledge the technologies’
effectiveness and a firm’s commitment to utilizing data to get valuable
insights to improve decision making. Once a business owner has determined the
goal of analysis, a methodology is selected, and data is obtained to support the
analysis.

Acquiring data usually involves extracting
from several sources and systems. Once the process is completed, data
integration and cleansing into one repository is done. Initially, a smaller
sample set of data is used for analysis. Some of the commonly used tools
include spreadsheets and data mining applications.

The deployment of predictive models involves
scoring data records that are usually found in a database. The scores are vital
for the optimization of real-time decisions within various processes in an
organization. On the other hand, business insights combine data and analysis to
understand the meaning and allow business owners to understand different
situations.

Top Emerging Trends in Data Analytics

Numerous emerging trends help organizations
navigate tough economic times, including the COVID-19 pandemic. The following
are some of the most common emerging trends in the industry.

Faster Artificial Intelligence

According to some analysts in the field, most
companies will have shifted from piloting to implementing artificial
intelligence. By doing so, there will be a five times increase in data
streaming and infrastructures. For example, some organizations are using
machine learning, and natural language processing approaches to obtain valuable
insights and understand the long-term impact of the current crisis.

Some AI techniques create flexible systems for
handling complex business situations. There have been significant investments
in chip architectures that are accelerating artificial intelligence and
workloads and reducing reliance on systems that may require high bandwidths.

Decision Intelligence

According to some experts in the field, a
significant percentage of large firms are expected to hire analysts for
practicing decision intelligence, which brings together multiple disciplines,
including decision management. It comprises applications in the field of
adaptive systems that involve multiple disciplines. Decision intelligence
offers organizations a framework for helping leaders to design, model, and
monitor decision models in the context of business outcomes.

Data Discovery and Visualization

The impact of data discovery has increased
significantly in recent months. According to a recent survey in the industry,
data discovery is one of the emerging trends. Business intelligence users have
shown that that empowerment is a strong trend.

The high demand for data discovery tools shows
a major shift in business intelligence to increase data usage and extracting
insights. The use of online data visualization tools in performing such actions
is becoming essential during decision making.

Predictive and Prescriptive Analytics

Business analytics of tomorrow focuses on the
future and aims to answer questions such as what will happen and how to make it
happen. Predictive and prescriptive analytics are some of the most common
topics among business analytics professionals.

This is because big data is becoming a
significant focus of analytics processes that large companies, small and
medium-sized businesses leverage. Predictive analytics involves extracting
information from data sets to forecast future possibilities.

On the other hand, prescriptive analytics
involves examining data or content to help business owners to know the
decisions that should be made and the steps they should take to achieve
organizational goals. This is often characterized by things such as machine
learning and graph analytics.

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