3-day Intensive Data Science Training: Three Pillars of Data Science

COURSE OVERVIEW: (Big Data Analytics, Data Management and Data Storytelling)

Three Pillars of Data Science: Big Data Analytics, Data Management & Data Storytelling with Isaac Reyes, Dominic Ligot and Dan Meyer

 Rock Stars of Data have joined forces to offer a unique training on the skills needed to build and develop a Data Science team here in the Philippines.

Everyone is rushing to hire Data Scientists and build Data Science Teams. However, many businesses in the Philippines are finding out that this is easier said than done. According to Big Data Expert Bernard Marr, “To build a strong, successful big data and Data Science team, organizations should focus less on finding candidates who are “perfect” on paper and direct their efforts more toward putting together a group that is greater than the mere sum of its parts.”

This seminar will involve hands-on use of common big data analytics tools such as Excel, Tableau and SQL. Having at least a basic understanding of data science will be helpful in order for attendees to get the most value out of the 3-day training.

LEARNING SESSION DESCRIPTION:

A Data Science team, carefully constructed with the right set of dedicated professionals, can prove to be an asset to any organization. It’s a fact that success of any project is dictated by the expertise of its resources and data science is no exception to this golden rule of thumb. Professionals with diversified skill-sets are required to successfully negotiate the challenges of a complex big data project.

 For your Data Science project to be on the right track, you need to ensure that the team has skilled professionals capable of playing several essential roles including a business analyst, a date warehouse expert and a data storyteller. The presence of these three experts, working together for a common goal, will result in the ability for your business to handle a variety of big data challenges.

LEARNING SESSION OBJECTIVES:

• Apply Cutting Edge Technologies to Organize, Interpret, and Summarize Big Data in Your Business
• Understand the components of The Data Value Chain and how they are all important to deriving value from data.
• Learn database manipulation and processing basics using the Structured Query Language (SQL)
• Connect a data analysis tool such as MS Excel or Tableau to a database to be able to perform analysis on processed and stored data
• Develop a Deeper Understanding of How Best to Deploy Analytics and Data Science Techniques Across an Organization

IN THIS SESSION, YOUR ORGANIZATION WILL BE ABLE TO USE:

• A framework for asking the right questions, allowing the ability to link analytics to business strategy
• Specific skills to effectively frame the problem you’re addressing to uncover key opportunities and drive growth
• How to simply and quickly amplify decision making by separating the signal from the noise
• Guidelines on best practices for linking visuals together into a cohesive story that concludes with actionable recommendations
• Applied examples regarding trend analysis, sampling, confounding variables and the statistical aspects behind data storytelling

IN THIS SESSION, PARTICIPANTS WILL BE ABLE TO USE:

• Learn the best practices for organizing, summarizing, and interpreting data to bring out patterns in data that were not apparent at first glance
• Create complete data stories and know how to present these stories in an engaging way to upper management
• Generate statistically robust data driven insights that inform decision making in the business setting
• Build stakeholder support for project initiatives using data
• Know how to select appropriate chart types for a given dataset (e.g. When to use a bar chart versus a pie chart, a line graph versus a bubble chart)

WHO SHOULD ATTEND:

• Business professionals who are involved in day-to-day analysis of data.
• Managers of analysts or staff who spend a significant amount of their time collecting, analyzing and reporting data.
• IT and Development Staff that work closely with business leaders and decision-makers.
• Executives and managers who want to create more engaging and impressive presentations with Excel and PowerPoint
• Professionals already working in analyst positions, including (but not limited to) positions involved with data preparation, data analytics, digital and marketing analytics, customer and market analysis

KEY TOPICS:

DAY ONE LECTURER: MR. DAN MEYER

Big Data Analytics and the Business Analyst 

Definition of Business Analyst. This role existed long before big data, and people in this role continue to perform an important function. They have intimate knowledge of your industry and your company, and analyze business-level data to produce actionable insights. Business analysts work with front-end BI tools related to the core business and interact with the higher management of an organization. They further analyze business-level data provided by the data storytelling experts to find out insights related to the organization’s core business interests.

Section One – Effectively Framing Big Data Projects

• Learn How to Successfully Define Business Questions,
• Understand How to Write Effective Business Requirements,
• Uncover the Most Important KPIs in Your Business,
• Optimize Your Use of MS Excel For Big Data Analytics,
• Learn How to Build Better Management Reports.

Section Two – Big Data—It’s Not Just Size That Matters

• Understand the 3 T’s of Analytics: Talent, Technique and Technology
• Describe the Importance of Effectively, Analyzing Big Data in Business Today,
• Develop a Visual to See All the Big Data in Your Business,
• Recognize When to Employ Descriptive, Predictive or Prescriptive Analytics,
• Establish Clear Objectives for Big Data Projects

Section Three – Empowering Data- Driven Decision-Making

• Articulate the Importance of Accurately Interpreting Data,
• Understand how to Mitigate and Analyze Risk, Uncertainty, And Probability,
• Deliver Findings from Big Data to Drive Decisions Within Your Organization.
• Apply a Process to Present Big Data Clearly to Management
• Keys to Empowering Others with Your Business Knowledge

Section Four – Using Business Intelligence Tools

• An Overview of BI Tools used for Big Data Projects,
• Tableau Public Demonstration,
• Discuss the Concepts of Data Visualization and Data Storytelling,
• Build A Business Dashboard Prototype,
• Tips on How to Make Your Data and Analysis More Enchanting

DAY TWO LECTURER: MR. DOMINIC "DOC" LIGOT

Engineering Data with a Data Warehouse Master

Definition of Data Engineer. The data engineer is concerned with the capture, storage, and processing of the data itself. The role of a data engineer is at the base of the pyramid. Data engineers constitute the foundation of a data science project and they are trusted with the responsibility of capturing, storing and processing the relevant data. Data Collection, Data Warehousing, Data Transformation and Data Analysis – these are typically handled by a team of data engineers. They ensure that all the raw data points are captured and processed correctly. The processed data is then handed over to the next group of people, the machine learning experts, for taking it further.

Section Five – Presenting the Data Value Chain and Databases

• Discuss the components of The Data Value Chain and the various users and roles involved in transforming data to value: Database and ETL engineers, Data analysts, Business users.
• Learn about basic data architecture and the role of databases in processing data.
• Understand the basics of databases, tables and views.
• Learn about the Structured Query Language (SQL) and SELECT statements.

Section Six – Data Processing with SQL

• Discuss the additional value that can be derived from using SQL for Data Processing.
• Go into detail on various ways of processing and preparing data using SQL.
• Learn about aggregates, conditions, how to join tables, and run queries within queries.

Section Seven – Accessing SQL Tables with Excel

• Learn about Open Database Connectivity (ODBC) and how Excel uses ODBC to connect to external data sources.
• Discover how SQL tables and views can be read by Excel into instant Pivot Tables and Pivot Graphs.
• Understand how changes in database table or view via SQL Inserts, Deletes, and Updates are reflected on Excel.

Section Eight – Performing analysis of SQL-based data using Excel

• Learn about how SQL data can be dissected using the Data Analysis functions in Excel.
• Talk about form tools and macros that can automate manual reporting.
• Discuss tips for reporting and sharing the results of your analysis.

DAY THREE: Mr. Dan Meyer and Mr. Doc Ligot

Data Storytelling with Data Science Experts

Definition of a Data Storyteller. These experts are equally statistically minded and artistically gifted, with experience in programming and building data models that can be visualized and turned into data stories. Data Storytellers must have excellent communication and presentation skills that’s are used in translating data analyses into layman’s terms in order to influence a business decision or action. Their job is to ensure that the derived information is not only well researched and accurate, but also understandable and easily used to explain what the data says in a compelling way.

REQUEST FULL COURSE OUTLINE HERE: [email protected] or visit sonicanalytics.com

LEARNING INVESTMENT

Early Bird Rate

P 18,000.00 + VAT/Pax

(Pay the full amount on or before June 10, 2017)

Group Rate

P19,500.00 + VAT/Pax

(Minimum of 5 members)

Regular Rate

P 21,900.00 + Vat/Pax

(Starting June 11, 2017)

All rates includes: 3-day Training, Venue, Training Modules, AM/PM Snacks, Lunch and Data Science Training Certificate of Completion. 

For inquiries: [email protected] | 0917-799-2827 (02) 959- 8017