Data Analytics Vs Data Science : Understand The Difference

If you are a learner to the big data industry, then i am damn sure you will be get confused with these two terms. That is data science and data analytics. These two terms seems to be pretty similar to each other, but as your secondary mind thinks, this two topics are having huge variations between them. So this article is for the novice people who are getting struggled to understand the difference between data science and data analytics..

The Similarity Between Data Science and Data Analytics

Before understanding the difference we have to fully accept the similarity between these two fields. Yes, these two fields are totally focused on analyzing the data. This is the only and primary similarity to both data science, and data analytics(business analytics). But, inside the data engineering cycle, this two process starts to vary between each of us, as they are occur in two different phases.

Data Analytics :

It is a systematic process, to extract valuable information’s various structured and unstructured data source. Getting the past, present and future business performance through collected business information’s. Determining and explaining the best statistical &data driven business model to the concern business owner

In simple terms :

Collecting, extracting, visualizing the business insights from various structured and unstructured business data, and helping business owners to take timely, data driven, and logical business decisions.

Data science :

Designing, developing, and deploying logical, automated, machine learning algorithms that should support any business intelligence tools inorder to analyze a huge volume of data. it is the foundation for data analysis, through which an applied business problem can be solved.

Image source : The Ultimate Comparison: Data Science vs Analytics

Originally published on : What is the difference between Data Science and Data Analytics?

How Does Big Data help For Business Growth?

Data sets that are too large to handle are known as big data. For enterprises and large scale businesses, it becomes a complex task to segment the huge volume of raw data.  So to rectify these issues Big Data have been introduced.

What is Big Data?

Big Data is a systematic data management process that treats a comprehensive approach with a high volume of both structured and unstructured data in order to bring better data insights.

Business intelligence helps business to visualize the limited amount of structured data that worked and not worked in the past. Big Data, let the entrepreneurs experience the exact business insights that will bring fruitful results in the future. Big Data with predictive analytics tells what steps should be made in the future to drive the business on the right path.

Big Data Analytics

It is a systematic approach. It examines the large variety of data sets, to unbox the hidden patterns, market trends, customer experience, data complexities, and business flow to make better-informed business decisions.

How big data helps in business growth?

None of the business launched to the market with a big amount of data in the initial stage, when the business grows as a brand, the data behind the business flow gets dumped in huge volume. So, Big Data is strictly suitable for large scale businesses that are in big need to manipulate or audit their business information.

Why business has to manage the data?

There are two reasons,

1. To segmentize in an easily readable, identifiable, trackable data, which we call as data modeling

2. To make better decisions, by analyzing the data and visualizing it with proper data visualization process.

If a business fails to do any one of the above, sure it will be tough for them to lead the business next level and will be tired of trapped into the data collections.

Data Analytics Processes

Big Data Analytics involves the following basic processes.

1. Data aggregation   -  Data collection.

2.  Data Cleansing      -  Filter out unwanted data.

3.  Data Modelling       -  Making the Data into easily identifiable data sets.

4.  Data warehousing  -  Storing the data into the warehouse.

5.  Data Visualization  -  Visualizing the data in a graphical manner.

6.  Visual Report Development - Developing visual reports.

In Future, we will discuss each process in detail.

Originally published on  : How Does Big Data help For Business Growth?

What Is Bibrainia?

Make strong business decisions with bibrainia’s big data & BI solutions.  At bibrainia, we make the complex business data into a simple, manageable, and trackable insights.

Why you should choose Bibrania - BI & Big Data Solutions?

Bibrainia, delicates the data complexities using advanced data engineering techniques. No matter how big your business data is, our expert consultants can dilute the data knots with advanced BI tools. We are expert in following big data solutions.

1. BI Consulting services

2. BI Reporting Services

3. Data analytics Services

4. Data warehousing services.

5. Data Visualization services

6. Predictive Analytics

7. Data Mining

We are expert in handling the following BI Tools

1. Apache Hadoop

2. Apache Spark

3. Qlik sense

4. Qlikview

5. Power BI

6. Tableau

We provide best data analytics solutions for anytype of industries from startup to big firms.

Let’s make your business data more powerful with bibrainia. 

Originally published On :  Bibrainia - A Hub of Big Data & BI Solutions.