After reading these many articles in this blog, I think you people were clear regarding the what is meant by data science and its applications in different fields. But there is no end to the application of data science. As long as we discuss there would be always one left to discuss. So today, I would like to introduce how data science takes part in SEO. This word SEO looks to be short. But it has a great subject. Today many companies were working only on SEO. And most of the MNC’s have SEO department. So, I think you people were clear regarding the importance of SEO in the IT industry.
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So when people talk about the search engine, it is a combination of Text, images, videos and so on. And when a user enters the particular keyword in the search engine, we do get several hundred of results ordering from 1 to 100. The order here depends on the algorithm used by the google. One of the algorithm that the Google uses today is K-means. And today most of the data scientists work on these algorithms for the effective and efficient retrieval of data. The data science algorithms will help the search engines in the following manner.
Data Exploration:
If you have a bulk amount with you, it can be easily uploaded into the cloud. Using different algorithms like k-means, data will be explored to the end user. Today most of the search engines were most friendly to the user. It means, these search engines do not care regarding the format type uploaded to it. It accepts different file formats like J SON , CSV, Excel, XML ,PDF images . audio etc. Moreover, it does not consider the amount of data being uploaded. It can be either dense (or) sparse. Once uploaded, these search engines have a vast query language that supports a ad-hoc querying.
Test /data validation :
Today many of the company customers have data science teams. And these people were using this search as simple as possible for easily. Moreover, most of the search engines support for complex join across multiple data sets as well as an easy selection of specific rows and columns.
Data reduction and feature selection engineering :
Today search engines come with a variety of tools by default. Moreover, it supports a variety of tools. These tools include the capturing tools and capturing metadata, imputing values and handling nulls. Additionally, they also support the search engine in a variety of languages other than English.
Search-driven analytics:
So till now, we have seen about the search engines and its working. But we can't stop here. Other than uploading and retrieving the data, we need additionally some analytics. This analytics is necessary to get the information regarding the number of users used this query. This analysis is necessary whether to continue with the current approach (or) to change to the other. Today we were using the most effective and efficient search engines. These help in regression analysis, trend analysis and do anomaly detection.
For example, it helps to get the information of liked and disliked people when a new product has started selling.
Tools will be own choice:
Today we have many developers in the industry. And each programmer can choose their own language depending on their own interest. Similarly, Google also allows you to choose the programming language as per the developers choice like Command line, (or) notebook (or) notebook, Python, R (or) Scala as per the developers choice.
Key value, columnar and mixed storage
In this decade, search engine operates as smart as humans. They do multiple activities like humans. Today search engines operate on key value and columnar data storage. Additionally, it beats all corners when it comes to mixed data(text + numeric+ categorical and special).
Recommended audience :
Software Developers
Project managers
Database Administrators
Prerequisites :
It good to have a basic knowledge of one of the programming languages like C, Java, Python. And the basic idea of storage programming like SQL, but not mandatory. Trainers will teach each and every topic if you do not have knowledge. Master in Data science from the real-time experts through Data Science Online Training.