Automation in Data science
Due to the advancement of Artificial Intelligence,
the automation capabilities of it have been expanded at a very high level. Many
innovations during automation are proving in changing complicated Artificial
Intelligence tasks into a way easy one. Automation process has already made
Artificial Intelligence tasks into easy ones, if totally not but most of it thought
for sure. Industry360 has contributed a lot into this space and thus ranked as
the best data analytics institute in india.
This full process includes knowing the
problem, then the collection of the data, processing of the data, exploration
of the data, analysis of the data gained, and then the sharing of that
processed information to various heads. Data
science is now an area of technology investment, given its impact on
customer experience, revenue generation, maximizing operations, efficient
supply chain, risk management and several other business functions.
Data science enables a data-centric
decision-making process for organizations, accelerating digital transformation
and AI initiatives. According to Gartner research only 4% of management
have implemented AI, and 46% are in the process. While investments
continue to grow, enterprises find it increasingly difficult to implement
and accelerate data science industry practices. Ranked as top analytics training institutes in india
Industry360 has partnered across manhu functional units to work on
implementation of the same.
Traditional
Data Science Process
There
are several challenges to the adoption and acceleration of data science in
enterprises. Industry DS projects are complex involving data collection,
data wrangling, feature engineering, machine learning, visualization and
production taking several months to complete even for an experienced
team.
It is a
highly collaborative process requiring specialized skill sets with domain
experts, data engineers, data scientists, business intelligence engineers, and software
architects. The bigger challenge lies in interpreting the outcome of most
enterprise data science projects making it difficult for business users to
implement.
Industry360
is a one stop shop for all your planning & execution in this space.We have
had the experience of overcoming challenges across domains in diversified
verticals. We have delivered our best in class sport & service to the
eminent organizations in this space.We also curate content and deliver it to
partner organizations for better transitions. We proudly rank as the best institute for
data science in delhi ncr.
What
Makes Data Science Hard?
Juggling
with machine learning (ML) models is considered to be the fun part, but the
pain point of any data science project is ETL and feature engineering. ML
operates on a single flat table called full of features. Given a feature data
scientists can play with ML algorithms. But actual enterprise data always
provide collection of many data tables with complex relationships.
Scaling
is the most difficult aspect of technology because it may backfire. The machine
learning models are good for showcasing and sit idle on the shelves but not
being used by many. We cater to bringing them to life and scalability. Our best institute for data science in india. revolve
around transmitting the information required with industry practices and enable
organization to embrace the scalable models over weak ones.
Data
required by machine learning vs. Actual enterprise source data
Last-mile
ETL and feature engineering are necessary steps to transform the collection of
tables into a feature table. These are the most challenging and time-consuming
steps in a data science project and require highly skilled data scientists and
domain experts – expensive and scarce resources.
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