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200 Hours

 

Career Path - Data Strategist

Learn how to manage the whole process of sourcing alternative datasets, working closely with quants, data scientists and portfolio managers.
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Save 56% Offer ends on 28-Feb-2023
Preview Career Path - Data Strategist course
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Data analysts take mountains of data and probe it to spot trends, make forecasts, and extract information to help their employers make better-informed business decisions. The career path you take as a data analyst depends in large part on your employer.

The role of the data analyst has become increasingly important during the internet age, with employment opportunities in industries ranging from finance to marketing to social media. In addition to knowing your way around computers, data analysts must also be well-versed in statistical methods and models. Big data and machine learning are among the cutting-edge applications of data analysis.

Data strategists manage the whole process of sourcing alternative datasets, often working closely with quants, data scientists and portfolio managers. They help to screen datasets to select those which are likely to show promise and fit the requirements of the business. Data strategists manage the whole process of sourcing alternative datasets, often working closely with quants, data scientists and portfolio managers. They help to screen datasets to select those which are likely to show promise and fit the requirements of the business. Quants and data scientists then test these shortlisted datasets in a rigorous process.

Business people know that foresight and good business strategy are essential for maintaining a competitive position. Data strategies are typically developed by business managers seeking buy-in from business leaders. On the other hand, data scientists and data engineers continue to generally have organizational alignment with IT or digital operations, even though the data strategy and vision will be developed by business people. Therefore, there is a current, and growing, need for a translational role between the data professional and business manager/leader.

Skills Required:

Data strategists need the technical skills to understand data. It isn’t necessarily about coding lots of Python every day or discussing the minutiae of a particular regression technique. Instead, it’s more about having the intuition to know which datasets are likely to be valuable for the firm’s trading style and to leave those which are likely irrelevant. Data strategists also need excellent soft skills, given that a data strategist acts as a bridge between the outside firms and internal clients such as data scientists and portfolio managers.

 

Course/Topic 1 - Business Intelligence and Data Analytics - all lectures

  • In this lecture session we discuss about Bi concepts, examples and application of business intelligence and data analytics and also cover other concepts of BI.

    • 14:48
  • In this lecture session we learn about basic concepts of BI and also cover factors of business intelligence in brief.

    • 19:22
  • In this lecture session we learn about data warehouse data access and data dashboarding and also cover presentation in BI.

    • 24:10
  • In this lecture session we learn about product database, advertise database and customer demographic database and also cover data analyst concepts.

    • 19:54
  • In this lecture session we learn about basic introduction of business intelligence and also cover factors of business intelligence in brief.

    • 31:10
  • In this lecture session we learn about introduction of predictive modeling and also cover functions of predictive modeling in brief.

    • 1:05:08
  • In this lecture session we learn about data related to customer services and also talk about customer relation databases in brief.

    • 32:37
  • In this lecture session we learn about introduction of NoSQL and also cover basic functions of NoSQL in business intelligence.

    • 33:46
  • In this lecture session we learn about graph stores and also talk about the advantages and disadvantages of graph stores in BI.

    • 25:52
  • In this lecture session we learn about hierarchical clustering in business intelligence and also talk about clustering factors in BI.

    • 29:58
  • In this lecture session we learn about introduction of salesforce in business intelligence and also talk about some basic uses of salesforce.

    • 34:25
  • In this lecture session we learn about introduction to NLP and also cover what is natural language processing in artificial intelligence.

    • 18:30
  • In this lecture session we learn about natural language processing speech to text conversion and also cover the importance of natural language processing.

    • 25:22
  • In this lecture session we learn about introduction of apache server in business intelligence and also talk about basics of apache server.

    • 44:24
  • In this lecture session we learn about deep drive into business intelligence and also talk about factors or deep drive in business intelligence.

    • 30:54
  • In this lecture session we learn about data warehousing in business intelligence and data analytics and also talk about factors and features of data warehousing.

    • 39:54
  • In this lecture session we learn about types of data in business intelligence and also talk about different types of data in BI.

    • 25:07
  • In this lecture session we learn about mobile BI and also talk about open source BI software replacing vendor offering.

    • 39:18
  • In this lecture session we learn about real time BI in business intelligence and also talk about factors of real time BI in brief.

    • 1:35:17
  • In this lecture session we learn about data analytics comprehensively and also talk about functions of data analytics.

    • 23:43
  • In this lecture session we talk about data analytics vs business analytics and also talk about the importance of data analytics.

    • 41:04
  • In this lecture session we learn about Embedded analytics and also talk about functions of Embedded analytics in data analytics.

    • 1:02:55
  • In this lecture session we learn about collection analytics and also cover the importance of collection analytics.

    • 59:03
  • In this lecture session we learn about survival analytics and also cover duration analytics in brief.

    • 29:35
  • In this lecture session we learn about machine learning techniques and also cover the importance and factors of machine learning techniques in business intelligence.

    • 37:34
  • In this lecture session we learn about geospatial predictive analytics and also talk about functions of geospatial predictive analytics in business intelligence.

    • 1:01:31
  • In this lecture session we learn about cohort analysis in data analyst and we also cover functions and importance of cohort analysis.

    • 21:36
  • In this lecture session we learn about data mining in business intelligence and also talk about data mining functions and why we need data mining in business intelligence.

    • 45:40
  • In these lecture sessions we learn about anomaly detection and also talk about functions of anomaly detection in brief.

    • 1:00:36
  • In these lecture sessions we learn about statistically sound association and also talk about factors of statistically sound association in business intelligence.

    • 31:29
  • In this lecture session we learn about cluster analysis. We’ll cover all types of cluster analysis in brief and also cover the importance of cluster analysis in business analysis.

    • 36:21
  • In this lecture session we learn about DBSCAN in business intelligence and also talk about DBSCAN functions and importance.

    • 59:58
  • In this lecture session we learn about regression models in business intelligence and also talk about the function of regression models.

    • 31:57
  • In this lecture session we learn about extraction based summarization in business intelligence and also cover all types of summarization in data analyst.

    • 10:57
  • In this lecture session we learn about machine learning in BI and also talk about factors and importance of machine learning in brief.

    • 1:00:50
  • In this lecture session we learn about machine learning vs BI we also discuss the basic difference between machine learning and business intelligence.

    • 1:15:37
  • In this lecture session we learn about how ml can make BI better and also talk about ml basic functions.

    • 1:18:01
  • In this lecture session we learn about data warehousing and also talk about how we manage data warehousing in business intelligence.

    • 18:28
  • In this lecture session we learn about data warehousing in business intelligence and data analytics and also talk about factors and features of data warehousing.

    • 29:22
  • In this lecture session we learn about data mart in business intelligence and also talk about data mart function.

    • 32:40
  • In this lecture session we learn about data dimensions in business intelligence and also cover all types of data dimension in BI.

    • 30:31
  • In this lecture session we learn about data dimension in business intelligence and also cover functions and importance of data dimension.

    • 24:02
  • In this lecture session we learn about data vault modeling in business intelligence and also cover different types of vault modeling in brief.

    • 29:14
  • In this lecture session we learn about links and satellites and also cover the importance and factors of links and satellites in business intelligence.

    • 28:59

Course/Topic 2 - SAP MDG - all lectures

  • In this first video on the SAP Master Data Governance course, you will be learning about the MDG Deployment Options like Co-Deployment and Hub Deployment along with the overview of High-Level Architecture. You will also be learning about the concepts like Work Centers, Roles, Change Request, Workflow-Linear and Workflow-Parallel and the Staging Area Usage.

    • 36:24
  • This video tutorial will teach you how to the complete work process of an SAP MDG Solution and how it is helpful for a business enterprise model. The trainer will also be showing how to work on the “Inactive Data Models” and the methodology of different MDG Solutions like Governance Integration, NWBC, ECC & HANA DB to name a few. Further, you will also be learning about the Simplified Process Flow of MDG.

    • 1:04:50
  • In this tutorial, you will be learning about the Simplified Process Flow in SAP MDG along with the Business Partner Attributes; the Supplier and Customer Attributes. Further, you will be learning about the HTML-based user interface, data flow, and replication and how MDG helps the Business User and with User Interface, Data Quality functions, Material Class and Hierarchy Maintenance, Robust Data Replication, Template Creation, Mass Maintenance, and the Analytical features for the processes.

    • 1:23:08
  • In this video, you will be learning about the 2 types of Deployment Options in the MDG system which are the Co-Deployment and Hub-Deployment options. The trainer will be seen explaining each and every detail in the difference between the two by taking examples of how it works in the real-time SAP MDG system.

    • 2:36:08
  • In this video, you will learn about the communication work process between the Hub Deployment and ECC System. The trainer will be seen explaining the complete workaround of how the Co-Deployment and ECC Operation System works.

    • 57:09
  • In this video, you will learn about the different entity types associated with the SAP MDG system. You will also be learning about the Root Table along with the MARA and the MARC table.

    • 09:37
  • In this tutorial, you will learn about the concept of Mapping in the MDG system along with the different types of attributes and their types. The trainer will be showing the complete work process of the mapping between them in the SAP system of the “Inactive Data Model” of the screen.

    • 1:33:04
  • In this tutorial, you will learn about the fundamental steps to configure a governance scenario like Data Model, User Interface, Change Request Process, User Access, and Using the newly created scenario. Further, you will be learning about the complete concept of the Data Model along with the Entity Types, SU Types Summary, and the Relationships with detailed explanation on the SAP system.

    • 41:12
  • This video is a complete practical training on how to create a Data Model in the SAP MDG system. You will be seeing a detailed practical demonstration of the same by the trainer in the system.

    • 52:09
  • In this video, you will be learning about the Business Rule Framework, its complete and detailed concept, Business Rule; Elements, Mode of Operations, Workflow Integration in BRF Plus. The trainer will be showing the BRF in the SAP system. Along with this, you will also be learning about the MDG UI configuration and under it parts like Business Activity, Logical Action, Change Request Type, and the CR Status.

    • 1:19:09
  • In this video, you will learn about the concept of Step Type and how it is configured. Along with this, you will also be learning about the prerequisites for BRF, what is BRF Workflow, its Key Elements, User-Agent Table, and a complete step-by-step process of how BRF Workflow works.

    • 1:36:06
  • In this video, you will learn about the Model to Dialog-Step-Agent Decision Table, Key Elements for Process Pattern like UI Dialog, Call Sub-Workflow, Call Data Replication, etc. You will be getting a detailed explanation of these Key Elements and also how all these works in the SAP MDG system.

    • 59:48
  • In this tutorial, you will learn about the Static Workflow Template which will be shown in the SAP system. Further, you will be knowing about Floor Plan Manager –its Component Structure, FPM Component Interfaces, Sample Structure of FPM, and lastly about the Fluid Editor which is the tool for working of the FPM in the MDG system.

    • 1:14:18
  • In this video, you will get complete practical knowledge on the FPM Workbench along with working on the Web Dynpro Application. The tutor will be seen explaining each and every step in the SAP MDG system.

    • 1:15:56
  • In this video, you will be learning about the concepts of BOL and Genile which stand for Business Object Layer and Generic Interface Layer resp. The trainer will be seen explaining these concepts taking examples of the practical scenarios; its work process and along with this the component configuration in the SAP MDG system.

    • 58:09
  • In this MDG tutorial, you will be learning about the concept of Roles; creating custom roles under Role Maintenance, change of roles, and others. Moreover, you will be learning about the nwbc screen elements under it concepts like adaptation, Feeder Class, etc and lastly, you will be seeing be having the knowledge on the various MDG UI Layers.

    • 1:05:01
  • In this video, you will learn about the steps involved under Personalization, Customizing and Configuration in the SAP MDG work process, with a detailed component configuration of the steps shown by the trainer in the SAP system.

    • 1:12:08
  • In this tutorial, the trainer will be seen explaining the various application programming contents, answering the queries of the students, and further you will get the knowledge of the Staging Table in SAP MDG.

    • 52:51
  • This video is all about the various concepts associated with the MDG relevant APIs, its history along with different types of APIs like Convenience API, Governance API, and the Abstraction Layer. You will also be learning about the Reading Entity Data the complete work cycle of the API in the MDG system.

    • 1:08:59
  • This tutorial is about how you can implement an access class to save data in the SAP MDG system. The trainer will be seen showing the step-by-step process of the implementation in the system.

    • 1:16:28
  • This MDG tutorial is a complete practical demonstration of the API Programming work process, in addition to another work process in the system like ABAP Debugger, Class Builder, etc. The trainer will be seen explaining all the concepts in the MDG system.

    • 1:01:52
  • This video is a small discussion on the previous MDG concepts being taught by the trainer throughout this course.

    • 04:04
  • This video is a quick recap on the Feeder Class; what is it and how it works in the SAP MDG environment, along with some system-oriented concepts related to it.

    • 29:59
  • In this video, you will be learning about the different activities associated with the SAP MDG module such as Analysing Application Log, Display Workflow, Process work items as Administrators, and others. Along with that, you will be getting an explanation on the Finance Accounting Governance with G/L account centrally and analyze log for outbound implementation.

    • 56:54
  • In this video, you will be learning an in-depth and detailed concept of the Data Replication process in the SAP MDG system, with hands-on working on the data models, structure, and mapping in the system. Further, you will be knowing about Defining Business Systems, Creating a Business Object Type in MDG system, and defining object nodes.

    • 1:21:13
  • In this tutorial, you will learn how to create and edit mappings in the MDG system. Furthermore, you will learn about the Service Mapping Tool, Defining Business Systems, Defining Object Nodes, Assigning Key Structures to Object Identifiers, Defining Filter Objects, and Creating Outbound Interface.

    • 2:13:37
  • In this video, you will learn about Customer Vendor Integration (CVI) and the key concepts associated with it, while showing it in the SAP system such as Synchronization Options, Set BP Role Categories for Customer Integration, Defining Vendor Link for Business Partner Roles and others. You will also be learning about the Web Service Configuration and the Replication Model in the SAP MDG module.

    • 1:15:14
  • This last video on the SAP MDG course will teach you how to define an outbound implementation, business objects, and Web Service Configuration in the SAP MDG system. You will be getting a detailed step-by-step process of the whole workflow.

    • 1:12:04

Course/Topic 3 - Data Science with Python - all lectures

  • In this video tutorial we will get introduced to Data Science and the integration of Python in Data Science. Furthermore, we will look into the importance of Data Science and its demand and the application of Data Science.

    • 1:01:14
  • In this video we will learn, all the concepts of Python programming related to Data Science. We will also learn about the Introduction to Python Programing, what is Python Programming and its History, Features and Application of Python along with its setup. Further we will see how to get started with the first python program.

    • 59:19
  • This video talks about the Variable and Data Types in Python Programming. In this session we will learn What is variable, the declaration of variable and variable assignment. Further we will see the data types in python, checking data types and data type conversions.

    • 27:05
  • This tutorial will help you to understand Data Types in python in depth. This video talks about the data types such as numbers, sequence type, Boolean, set and dictionary.

    • 55:27
  • This tutorial talks about the Identifier, keyword, reading input and output formatting in Data Science. We will learn about what is an identifier and keywords. Further we will learn about reading input and taking multiple inputs from a user, Output formatting and Python end parameter.

    • 49:19
  • This tutorial talks about taking multiple inputs from user and output formatting using format method, string method and module operator.

    • 44:09
  • This tutorial talks about the Operators and type of operators. In this session we will learn about the types of operators such as arithmetic, Relational and Assignment Operators.

    • 27:52
  • This tutorial talks further about the part 2 of operators and its types. In this session we will learn about the types of operators such as Logical, Membership, Identity and Bitwise Operators.

    • 31:22
  • In this video you will learn about the process of decision making in Data Science. Furthermore, this tutorial talks about different types of decision-making statements and its application in Data Science.

    • 45:23
  • In this video tutorial we will learn about the Loops in Python programing. We will cover further the different types of Loops in Python, starting with: For Loop.

    • 32:47
  • In this session we will cover the further part of loops in Python programming. The type of loops explained in this video is: While loop and nested loop.

    • 39:43
  • In this session we will cover the further part of loops in Python programming. The type of loops explained in this video is: break, continue and pass loops

    • 23:13
  • In this video tutorial we will start explaining about the lists in Python Programming. This tutorial talks about accessing values in the list and updating the list in Data Science.

    • 46:54