Big Data

Training Courses, Workshops and Seminars

big data – extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions. These data sets are typically growing exponentially.
much IT investment is going towards managing and maintaining big data

Big data training is around methods, software and platforms that provide ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.

Advanced Implementation of Big Data Analytics with Graph Processing

2021-07-16T02:17:01+00:00June 24th, 2019|Tags: |

There are a significant number of big data analytics opportunities where graph processing is an effective model of computation for problem solving. In this workshop we present a programming model for implementation of graph algorithms and explain how the execution model works. We also provide example applications in the area of social network analysis, product cross-selling, and fraud detection.

How to Innovate in the Age of Big Data

2021-07-16T02:09:58+00:00June 24th, 2019|Tags: |

The era of Big Data presents exciting opportunities for leveraging analytics to create competitive advantage and new sources of revenue. To maximize business value, however, an enterprise must innovate in the context of good governance models to avoid technology projects for the sake of technology. In this workshop we describe a framework developed at the Massachusetts Institute of Technology for maximizing business value with the right combination of innovation and governance. We will examine new scenarios for monetising from Big Data sources. We will also explore opportunities for exploiting non-traditional data types from both internal and open data sources.

Smart Cities Using Big Data

2021-07-19T01:46:01+00:00June 24th, 2019|Tags: |

The use of big data is a lynch pin in the deployment of smart cities of the future. The potential of big data goes far beyond the efficiencies that can be created in areas such as energy consumption, health care, education, and law enforcement. The true potential of big data is directly engaging society in governance through increased transparency and delivery of services using access to data as a foundation. This workshop will provide mini-case studies in a range of settings from developed countries such as the USA and developing countries such as Pakistan. An emphasis of the discussion will be on how city governments can use data to improve quality of life for their citizens.

Big Mistakes to Avoid When Performing Big Data Analytics

2021-07-16T05:44:20+00:00June 24th, 2019|Tags: |

Mark Twain, a famous American author, once stated that there are “Lies, Damned Lies, and Statistics.” This phrase is used to describe the persuasive power of numbers, particularly the use of statistics, to lead people to draw incorrect conclusions. This workshop describes the subtle mistakes that can easily be made when interpreting the results from an analytic study or report. We describe logically sound processes for deciphering data using methods designed to illuminate actionable information for data scientists without distracting or misleading the knowledge worker from the relevant facts needed for effective decision-making.

Real-Time Analytics Development and Deployment

2021-07-23T01:02:51+00:00May 31st, 2019|Tags: , , , , , |

Real-time analytics is rapidly changing the landscape for deployment of decision support capability. The challenges of supporting extreme service levels in the areas of performance, availability, and data freshness demand new methods for data warehouse construction. Particular attention is paid to architectural topologies for successful implementation and the role of frameworks for Microservices deployment. In this workshop we will discuss evolution of data warehousing technology and new methods for meeting the associated service levels with each stage of evolution.

Innovating with Best Practices to Modernise Delivery Architecture and Governance

2021-07-23T01:01:04+00:00May 20th, 2019|Tags: , , , , , |

Organisations often struggle with the conflicting goals of both delivering production reporting with high reliability while at the same time creating new value propositions from their data assets. Gartner has observed that organizations that focus only on mode one (predictable) deployment of analytics in the construction of reliable, stable, and high-performance capabilities will very often lag the marketplace in delivering competitive insights because the domain is moving too fast for traditional SDLC methodologies. Explorative analytics requires a very different model for identifying analytic opportunities, managing teams, and deploying into production. Rapid progress in the areas of machine learning and artificial intelligence exacerbates the need for bi-modal deployment of analytics. In this workshop we will describe best practices in both architecture and governance necessary to modernise an enterprise to enable participation in the digital economy.

Modernising Your Data Warehouse and Analytic Ecosystem

2021-07-23T01:01:37+00:00May 20th, 2019|Tags: , , , , |

This full-day workshop examines the emergence of new trends in data warehouse implementation and the deployment of analytic ecosystems.  We will discuss new platform technologies such as columnar databases, in-memory computing, and cloud-based infrastructure deployment.  We will also examine the concept of a “logical” data warehouse – including and ecosystem of both commercial and open source technologies.  Real-time analytics and in-database analytics will also be covered.  The implications of these developments for deployment of analytic capabilities will be discussed with examples in future architecture and implementation. This workshop also presents best practices for deployment of next generation analytics using AI and machine learning. 

Cost-Based Optimisation: Obtaining the Best Execution Plan for Complex Queries

2021-07-23T01:00:08+00:00May 20th, 2019|Tags: , , , |

Optimiser choices in determining the execution plan for complex queries is a dominant factor in the performance delivery for a data foundation environment. The goal of this workshop is to de-mystify the inner workings of cost-based optimisation for complex query workloads. We will discuss the differences between rule-based optimisation and cost-based optimisation with a focus on how a cost-based optimization enumerates and selects among possible execution plans for a complex query. The influences of parallelism and hardware configuration on plan selection will be discussed along with the importance of data demographics. Advanced statistics collection is discussed as the foundational input for decision-making within the cost-based optimiser. Performance characteristics and optimiser selection among different join and indexing opportunities will also be discussed with examples. The inner workings of the query re-write engine will be described along with the performance implications of various re-write strategies.

Optimising Your Big Data Ecosystem

2021-07-23T01:02:03+00:00May 18th, 2019|Tags: , , , , |

Big Data exploitation has the potential to revolutionise the analytic value proposition for organisations that are able to successfully harness these capabilities. However, the architectural components necessary for success in Big Data analytics are different than those used in traditional data warehousing. This workshop will provide a framework for Big Data exploitation along with recommendations for architectural deployment of Big Data solutions.

Agile Data Management Architecture

2021-07-23T00:57:04+00:00May 18th, 2019|Tags: , , , |

This full-day workshop examines the trends in analytic technologies, methodologies, and use cases. The implications of these developments for deployment of analytic capabilities will be discussed with examples in future architecture and implementation. This workshop also presents best practices for deployment of next generation analytics.

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