Data science it powerpoint presentation slides

Slide 1: This slide introduces Data Science. State Your Company Name and begin.
Slide 2: This is an Agenda slide. State your agendas here.
Slide 3: This slide shows Table of Content for the presentation.
Slide 4: This is another slide continuing Table of Content for the presentation.
Slide 5: This is another slide continuing Table of Content for the presentation.
Slide 6: This slide presents current situation of our business by displaying the ratio of unstructured and structured data stored in the database.
Slide 7: This slide shows how unstructured data is causing challenges and how data science will help provide solutions.
Slide 8: This slide displays Table of Content for the presentation.
Slide 9: This slide represents the need of the data science in the organization.
Slide 10: This slide shows Benefits of Data Science to the Organization.
Slide 11: This slide presents the role of data science in decision making, and it includes collection & acquisition, storage, cleaning of data, etc.
Slide 12: This slide shows Table of Content for the presentation.
Slide 13: This slide displays the prerequisites for data science that include knowledge of machine learning, modeling, statistic, database, and programming languages.
Slide 14: This slide represents Data Scientist Must Have Skills Before Implementing Data Science.
Slide 15: This is another slide showing Data Scientist must have Skills before Implementing Data Science.
Slide 16: This slide presents Table of Content for the presentation.
Slide 17: This slide describes the life cycle of data science, which includes the stages such as predefined business problems, information acquisition, etc.
Slide 18: This slide displays the first phase of data science that is understanding business problems and the facts that come under this phase.
Slide 19: This slide represents the data preparation phase of data science, including its various stages such as raw data, structure data, data preprocessing, EDA, etc.
Slide 20: This slide shows Information Acquisition in Data Preparation Phase.
Slide 21: This slide presents model planning phase in data science and shows its tools, such as SQL Analysis Service, R, and SAS/ACCESS.
Slide 22: This slide shows exploratory data analysis in the model planning phase of data science and its various stages and reasons.
Slide 23: This slide displays various tools that could help in data modeling such as SAS enterprise miner, SPCS modeler, MATLAB, etc.
Slide 24: This slide represents operational phase of data science and what tasks are performed in this phase.
Slide 25: This slide shows last phase of the data science and in this phase, all the key findings are communicated to stakeholders.
Slide 26: This slide presents how data scientists throughout the project manage data till completion.
Slide 27: This slide shows Table of Content for the presentation.
Slide 28: This slide displays top tools that are used in data science which include SAS, Apache Spark, Excel, etc.
Slide 29: This slide represents Statistical Analysis System used in data science for data management and modeling.
Slide 30: This slide shows Apache Spark tool used in data science and its features such as speed, reusability, advanced analytics, etc.
Slide 31: This slide presents excel tool used in data science and its usage along with its features.
Slide 32: This slide shows tool used in data science and its features such as licensing views, subscription of others, etc.
Slide 33: This slide displays Tools for Data Science- Natural Language Toolkit (NLTK).
Slide 34: This slide represents TensorFlow tool used in Data Science, and its features include flexibility, columns, visualizer, etc.
Slide 35: This slide shows Table of Content for the presentation.
Slide 36: This slide presents difference between data science and data analytics based on skillset, scope, exploration and goals.
Slide 37: This slide shows difference between Business Intelligence and Data Science based on the factors such as concept, scope, data, etc.
Slide 38: This slide displays Table of Content for the presentation.
Slide 39: This slide represents tasks performed by the business analyst and how he will be helpful to improve business operations.
Slide 40: This slide shows data engineers’ responsibilities and skills that they should possess.
Slide 41: This slide presents tasks performed by a Database Administrator and skills that he should possess.
Slide 42: This slide shows machine learning engineer’s tasks and skills, including a deep knowledge of machine learning, ML algorithms, and Python and C++.
Slide 43: This slide displays the tasks performed by data scientists in data science and their skills.
Slide 44: This slide represents the different types of data scientists, including vertical experts, stat DS managers, generalists, etc.
Slide 45: This slide shows data architect’s tasks in data science projects and their skills.
Slide 46: This slide presents tasks performed by a statistician in data science and his skills such as data mining, distributive computing, etc.
Slide 47: This slide shows tasks performed by the business analyst and how he will be helpful to improve business operations.
Slide 48: This slide displays tasks performed by a data and analytics manager and skills he should have.
Slide 49: This slide represents RACI matrix for data science and tasks performed by data analysts, data engineers, data scientists, etc.
Slide 50: This slide shows Table of Content highlighting Checklist for Effective Data Science Integration in Business.
Slide 51: This slide presents Checklist for Effective Data Science Integration in Business.
Slide 52: This slide shows Table of Content highlighting Timeline for Data Science Implementation in the Organization.
Slide 53: This slide displays Table of Content highlighting Timeline for Data Science Implementation in the Organization.
Slide 54: This slide represents Table of Content highlighting Roadmap to Integrate Data Science in the Organization.
Slide 55: This slide shows Roadmap to Integrate Data Science in the Organization.
Slide 56: This slide presents Table of Content highlighting 30-60-90 Days Plan for Data Science Implementation.
Slide 57: This slide shows 30-60-90 Days Plan for Data Science Implementation.
Slide 58: This slide displays Dashboard for Data Science Implementation.
Slide 59: This slide represents dashboard for data integration in the business, and it is showing real-time details about expenses, profits, margins percentage, etc.
Slide 60: This slide shows Table of Content highlighting Impacts of Data Science Integration in the Organization.
Slide 61: This slide presents Impacts of Data Science Integration in the Organization.
Slide 62: This slide shows Table of Content for the presentation.
Slide 63: This slide displays Domains where Data Science is Creating its Impression.
Slide 64: This slide represents data science in healthcare departments and its benefits in different ways.
Slide 65: This slide shows Data Science in Logistics and Transportation Department.
Slide 66: This slide presents data science role in airlines and its benefits that cover revenue management and route planning.
Slide 67: This slide shows application of data science in financial organizations and its benefits.
Slide 68: This slide displays the data science application in business and its benefits.
Slide 69: This slide represents Table of Content for the presentation.
Slide 70: This slide shows the meaning of data science and how this innovation is helpful in businesses developing AI systems.
Slide 71: This slide presents critical components of data science such as data, programming, statistics & probability, etc.
Slide 72: This slide shows Icons for Mood Board for Data Science.
Slide 73: This slide is titled as Additional Slides for moving forward.
Slide 74: This is About Us slide to show company specifications etc.
Slide 75: This is Our Mission slide with related imagery and text.
Slide 76: This slide presents Venn diagram with text boxes.
Slide 77: This is a Timeline slide. Show data related to time intervals here.
Slide 78: This is a Thank You slide with address, contact numbers and email address.