Big Data Analytics Strategy for 2018: Enabling Your Business for the Future

As the year 2018 quickly approaches most of us are faced with having more data than we know what to do with. Big data creation, collection and applications have influenced business decisions more than ever in 2017, and as advances in artificial intelligence, predictive analytics, and machine learning continue to amaze, 2018 will be even bigger.

The truth is that the amount of data available to help run your business is greater than ever before. To effectively use this information, managers must consider the practical side of big data…what matters to you is how do you grow and build a team to make smarter decisions.

Much of the information out there just discusses the promise of the data deluge. The challenge is not the volume of data but rather the judgment needed to use it.

The truth is that the amount of data available to help run your business is greater than ever before. To effectively use this information, managers must consider the practical side of big data…what matters to you is how do you grow and build a team to make smarter decisions.

This seminar goes beyond the qualitative side of data analysis to explore proven quantitative techniques and technologies for identifying, inventorying and integrating data, so that more informed and reliable business decisions can be made.

With that in mind, DMAIPH has created a learning session entitled: Big Data Analytics Strategy for 2018: Enabling Your Business for the Future.

Learning Session Objectives:

  1. Apply Best Techniques and Cutting Edge Technologies to Organize, Interpret, and Summarize Quantitative Data
  2. Create a Process to Analyze Data and Identify Patterns Not Apparent at First Glance
  3. Reduce “Analysis Paralysis” and Go from Hard Data to Well-Reasoned Conclusions in Less Time

In this session, your organization will be able to use:

  • Specific skills to effectively frame the problem you’re addressing to uncover key opportunities and drive growth
  • Critical marketing steps of orientation necessary before engaging tools and technology
  • Strategies to simply and quickly amplify decision making by separating the signal from the noise
  • A framework for asking the right questions, allowing the ability to link analytics to business strategy

Who Should Attend: All business professionals who need the basic tools to quantitatively and accurately analyze the mountains of data that come across their desk each minute of every day. Managers of analysts or staff who spend a significant amount of their time collecting, analyzing and reporting data.

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

  • Agree on A Definition of What Is Big Data,
  • Identify Who Uses Big Data,
  • Describe the Importance of Effectively,
  • Analyzing Big Data in Business Today,
  • Come Up with A Data Map to Analyze the Big Data in Your Business,
  • Establish Clear Objectives When Analyzing Big Data

Section Two – Big Data – How to Collect It and Where to Store It

  • Recognize and Apply Various Data Collection Methods,
  • Identify and Resolve,
  • Problems Associated with Data Collection,
  • Consider the Various Types of Data Storage,
  • Examine the Difference Between Data Warehouses and Data Lakes,
  • Determine When to Use Data Blending in Your Analysis

Section Three – Assess Your Current Analytics Culture

  • Define What Is an Analytics Centric Culture,
  • Describe the Issues and Trends in Today’s Analytics Field,
  • Discover How to Find the Most Important KPIs,
  • Learn How to Build Better Management Reports,
  • Optimize Your Use of MS Excel For Big Data Analytics

Section Four – Using Business Intelligence Tools

  • An Overview of BI Tools,
  • Tableau Public Demonstration,
  • Discuss the Concept of Data Visualization,
  • Learn How to Use Infographics,
  • Build A Business Dashboard Prototype

Section Five – Interpreting Your Data and Analysis 



  • Articulate the Importance of Accurately Interpreting Data,
  • Determine How to Validate Your Data Analysis,
  • Mitigate and Analyze Risk, Uncertainty, And Probability,
  • Spot Patterns and Trends Through Statistical Analysis,
  • Understand How to Conduct Correlation Analysis and Regression Testing

Section Six – Deploying the Four Types of Analytics

  • Understand How We All Use Descriptive and Diagnostic Analytics,
  • Plan A Strategy to Use Predictive Analytics,
  • Think About When It Would Benefit to Use Prescriptive Analytics,
  • Recognize When to Employ Descriptive, Diagnostic, Predictive or Prescriptive Analytics,
  • Build a Data Model Prototype

Section Seven – The Art of Presenting Big Data

  • Apply a Process to Present Big Data Clearly,
  • Select the Appropriate Presentation Format,
  • Communicate Your Findings Effectively to Your Audience,
  • Determine Which Visual to Use,
  • The Key Elements of Data Storytelling

Section Eight – Marketing Your Big Data Analytics

  • Always Be Closing with Big Data Analytics,
  • Master the Power of Enchantment,
  • Being Decisive with Your Analysis,
  • Data Storytelling Case Study: The Best NBA Team of All-Time!
  • Use Findings from Big Data to Drive Decisions Within Your Organization

Case Studies and Exercises

We will use several case studies throughout the two-day class. One will be from Wells Fargo Bank on how they successful launched a new product using predictive analytics and data storytelling. Another case study will be using an example from Hewlett Packard (HP) and how they used predictive analytics to reinvent their talent management process.

In addition, to the case studies, attendees will participate in eight group exercises, one for each section of the two-day course. These exercises will use elements from the case studies as we progress from finding data, to conducting analysis on the data and finally presenting the data.

Learning Session Process

Too often people dive into the data only to be lost in haze of data. Case studies, hands on exercises and real life scenarios like the ones used in the training will give attendees the practical application they seek. This discussion will be pragmatic and pertinent to analysts, professional using analytics and managers of analysts across all industries.

 

Analytics Training – DMAIPH offers a wide range of analytics centric training solutions for professionals and students via public, in-house, on-site, and academic settings. We tailor each training event to meet the unique needs of the audience. If you need empowerment and skills enhancement to optimize the use of analytics in your organization, we are here to help.

Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation to learn which of our DMAIPH analytics training solutions is best for you.

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