Big data analytics: Discovering hidden patternsSoftware TrainingUpdated on Nov 25, 2016 View more like this | Visit India, UN | Contact Xebia India Training |
The big data analytics, a great concept for most of the organization if they want to capture all data that streams into their business. They can investigate their data and can get significant value from it. This process is used from old times to get insight to uncover things and new trends.Years before business used gathered information, run analytics and unearth information that helps them in future decision making but today businesses use data insights for immediate decisions. The main benefit of big data analytics is speed and efficiency.
Faster working style and agile methods gives businesses a competitive edge that they lack before big data analytics. According to most of top analytics executives in India, the biggest challenge is lack of analytic talent. Finding trained and responsible analytics workforce in India is a nightmare for employers. Thus to bridge the gap of this supply side between the employers and employees, a number of institutes have sprouted in the country that offers big data analytics course and develops analytics that have quality and business intelligence. These institutes train the candidates and make them employable for a career in business intelligence and business analytics industry.
Data scientists, modelers and analytics professionals can analyze large volume of transaction data that will help your business in making more important and informed business decisions. With Big data analytics course, you can analyze your data and get solutions almost instantly, which can slow down your effort with more traditional business intelligence solutions.
Learning Outcomes of the course:
This course is about discovering knowledge in database, searching a large volume of raw data to gather information patterns that are useful and are essentially embedded in the raw data.
Data scientists and decision makers use this information for new advantages and for developing new business models. A student can perform many tasks after completing this big data analytics course.
• Segment Customer- segmenting their customers through their purchasing habits.
• Target marketing- in which they try to recognize customer who are loyal or the customers who shows potential loyalty.
• They understand the customer thinking by estimating like what is the best product to up sell to a customer after they purchase a product, or what volume of visits can be expected on the website next week.
• Identify groups with similar characteristics.
• What is estimated customer lifetime value of each customer?
• Predicting customer churn in a telecommunication company.
Course coverage:
• Data science and data mining:
Introduction to big data, data exploration and data clearing.
Data visualization and story telling with Rstudio, python.
Data pre-processing, integration and data transformations.
Business forecasting, exponential smoothing, holt-winters smoothing.
• Projects in machine learning:
Experiencing a number of industrial projects.
Weekly exercises- students executing projects while implementing techniques learnt.
Projecting the next destination of a visitor.
Product classification challenge.
Sales revenue prediction.
Predict handwritten digits.
Standard customer satisfaction.
Advance regression techniques.
• Hadoop based analytics:
Hadoop eco-system.
Developing familiarity with Hadoop file system/ Hadoop cluster.
Data extraction with Hive, Pig, Tez and Impala using SQL.
Frequent itemset mining and data exploration and developing predictive analytical models on BigML Cloud.
Faster working style and agile methods gives businesses a competitive edge that they lack before big data analytics. According to most of top analytics executives in India, the biggest challenge is lack of analytic talent. Finding trained and responsible analytics workforce in India is a nightmare for employers. Thus to bridge the gap of this supply side between the employers and employees, a number of institutes have sprouted in the country that offers big data analytics course and develops analytics that have quality and business intelligence. These institutes train the candidates and make them employable for a career in business intelligence and business analytics industry.
Data scientists, modelers and analytics professionals can analyze large volume of transaction data that will help your business in making more important and informed business decisions. With Big data analytics course, you can analyze your data and get solutions almost instantly, which can slow down your effort with more traditional business intelligence solutions.
Learning Outcomes of the course:
This course is about discovering knowledge in database, searching a large volume of raw data to gather information patterns that are useful and are essentially embedded in the raw data.
Data scientists and decision makers use this information for new advantages and for developing new business models. A student can perform many tasks after completing this big data analytics course.
• Segment Customer- segmenting their customers through their purchasing habits.
• Target marketing- in which they try to recognize customer who are loyal or the customers who shows potential loyalty.
• They understand the customer thinking by estimating like what is the best product to up sell to a customer after they purchase a product, or what volume of visits can be expected on the website next week.
• Identify groups with similar characteristics.
• What is estimated customer lifetime value of each customer?
• Predicting customer churn in a telecommunication company.
Course coverage:
• Data science and data mining:
Introduction to big data, data exploration and data clearing.
Data visualization and story telling with Rstudio, python.
Data pre-processing, integration and data transformations.
Business forecasting, exponential smoothing, holt-winters smoothing.
• Projects in machine learning:
Experiencing a number of industrial projects.
Weekly exercises- students executing projects while implementing techniques learnt.
Projecting the next destination of a visitor.
Product classification challenge.
Sales revenue prediction.
Predict handwritten digits.
Standard customer satisfaction.
Advance regression techniques.
• Hadoop based analytics:
Hadoop eco-system.
Developing familiarity with Hadoop file system/ Hadoop cluster.
Data extraction with Hive, Pig, Tez and Impala using SQL.
Frequent itemset mining and data exploration and developing predictive analytical models on BigML Cloud.
