Data-Driven Analytics & Best Practices for Your
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Big Data Analytics is no longer a technology, but the premise for your business strategy. Combining the insights attained from the analytics with your big corporate goals, you can achieve greater heights, scale your business, and improve your performance. The data-driven strategies help you win a war waged against your competitors, and hold your competitive edge.

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Data-Driven Analytics & Best Practices for Your Business

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Data driven analytics best practices for your business

Data-Driven Analytics & Best Practices for Your

Business

Big Data Analytics is no longer a technology, but the premise for your

business strategy. Combining the insights attained from the analytics with

your big corporate goals, you can achieve greater heights, scale your

business, and improve your performance. The data-driven strategies help

you win a war waged against your competitors, and hold your competitive

edge.

When it comes to incorporating Big Data to your business, you need to have

a highly competent strategy in place, one that can help you attain your

goals while securing your business needs. Data for the businesses come

from all shores available, which is why you need to tame the data and

identify ones that suit your purpose best. Your enterprise should have the

capabilities to actually optimize this data and come out with the necessary

predictive and analysis models that can help you unleash the power of this

data. Finally, you need to have a decision making model that is transpired

from this model to improve the conduct of your business to improve the

returns.


Data driven analytics best practices for your business

As an organization that is working with data-driven analytics for your

business, you need to realize a few things and incorporate a few best

practices. This will help you yield better returns.

For a truly business driven data analytics, here are best practices that you

ought to follow.

Think your Questions

Before sourcing the data, it is important to start thinking the questions that

you aim for the data to answer. Data analytics is an answer to the questions

that determine your business strategy. You need to question what exactly

drives the demand for your product or service. Check for price and

availability (raw materials, other related industry products) that will

change or evolve with time. Regional factors and the role they play in the

sales of your products or services. Forecasts and predictions, how do they

affect your business? These are the questions that the data for your

business needs to answer. Basically, you need to combine your data with

your business in order to make it relevant to your needs.

Identify your Data Sources

You need to find the best data sources that can help you answer the

questions to your data. There is a whole load of data available at this

moment, which is increasing by seconds. Opportunities available with the

data are also ever evolving, which is why you need to not only choose your

data carefully but also make sure you are working with the right data

sources. When choosing data sources, you should take both panoramic and

granular views of your business setup with an aim to improve operations,

experiences and define winning strategies. Historical data is just an aspect

that businesses should consider; beyond that businesses should look into

data that gives them a purview into external factors.

Document Data

When you are planning to align data analytics with your business, it is a

good practice to document the data and make it discoverable. There will be

times when you have data that you didn't know would be useful to the

business. Documenting it would make it available to you at all times. Apart

from documentation, making it discoverable helps you search and locate

the data at just the right time. A data catalogue with all the right labels and


Data driven analytics best practices for your business

marks will help you identify the data, and use it appropriately at the right

time. Source of the data and source-within-a-source of the data is also

revealed with the documented data. This helps in availing a data just in

time to make critical business decisions.

Check for Data Quality

Many times you end up using data that has not been checked for quality.

How can you make reliable decisions with such data? You need a data

quality manager who can check into the quality of the data, and suggest if

this data can be used or not. The data needs to be continuously audited for

the quality of information, and incorporating the metrics that will help in

identifying how recent and useful the information in the data is. The idea is

to make sure the information is same through the various reporting

systems.

Automate Decision Making

Once you have standardized the data, and ensured it is centralized and

available in real-time, the next task is to automate decision making to make

sure you don't cause delay in taking critical decisions. The idea is to make

the insights available in real-time in a constant manner, thus suiting

decision making. The data-driven businesses are repetitive, automated and

systematic in nature, ensuring no response delay and improving efficiency

of the systems.

Engage Key Decision Makers

Last but certainly not the least, you should engage key decision makers by

showcasing progress, using visual analytics. The person whose decision

matters should be engaged early on so that critical decision making is

possible without any interruption. Expert feedback, similar decisions and

available data sources can help the key decision makers in thinking about

their decisions and enhancing upon them. The evolving nature of data and

business requires continuous feedback from experts.

This Article is Originally Published at Seashore Partners Official Blog


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