BI Geek

Who we are

Our vision

BI Geek is a company created in 2015 by a group of professional experts in Business Intelligence.

The outcome of the company is to take the consultancy original values and to provide real added value to our clients.

We believe that through specialization is the proper way to offer the best possible service.This is why we are exclusively dedicated to projects based on traditional architectures - Data Warehouse - and Big Data.

We are currently located in Madrid, Mexico DF and Boston.

Our main clients are focused on the financial sector.

Specialization

In the area of Information Technology (IT), the exponential growth of technology over the recent years has been especially notable.

New tools allow the resolution of data paradigms, both in volume and processes which, until now, they were unapproachable.

As a company, we have set out the challenge of specializing ourselves in this area, with the main goal of narrowing the gap between business and technology, achieving the effective application of the best technical solutions.

The Mirai Group

Mirai Group is composed of several companies specialized in different areas of services with a strong corporate culture and common values focused on obtaining maximum added value for customers.

BI Geek was born in 2015 with the aim of creating a new specialized practice within the group: the design and development of Business Intelligence systems.

BI Geek Group growing

2013
2014
2015

Services

Business Analysis

Identification of how Business Intelligence solutions can be holistically applied for the functional improvement of the business.

Business analysis is the starting point where the final solutions are built, The success of the project rely on this phase.

In BI Geek, the combination of technological and functional knowledge allows us to understand the real needs of the user and IT departments. According to this methodology, we position ourselves as interlocutors linking the two sides to define the lines of action that guarantee the goals and objectives of the client.

Understanding how an organization works, its policies, operations and internal infrastructures are imperative to meet the needs of the business. Based on this analysis, the solutions may consist on the implementation of new development components, improvements of existing processes or organizational changes.

The ability to make the right decisions, quickly and accurately, accompanied by a strategic plan based on the knowledge of the business are the keys that make the difference in the race to success, giving companies the competitive advantage that they pursue.

Solutions Design

Design of architectures in order to respond to business needs. Study of best practices, market tools and procurement strategies.

For BI Geek there is no generic solution applicable to all cases, the success of our projects lies on designing concrete solutions for specific cases.

Once the business needs are identified, our designs meet the different requirements of the customer, differentiating us in our capacity of adaptability to the different environments and situations. Our method allows to apply strategies to measure according to implementation times, costs and technologies.

Our solutions encompass Big Data services, classic Business Intelligence architectures and mixed designs, combining the potential of both options.

We are experts in the design and development of complete solutions, based on the most advanced technologies in the market, both in databases, in the development of distributed applications, ETL tools and reporting, mining and data exploitation, analytical prediction...

Business Intelligence

Development of projects based on traditional technologies, such as Power Center, Oracle, Tableau, Qlik View, ... Based on DW architectures as defined by Inmon or Kimball.

For solutions based on traditional Business Intelligence technologies, we offer analysis, design, development and implementation of the main technologies in the sector.

Taking the William Inmon DW2.0 architecture as its most robust - although simplified architectures can be applied - the following components diffe.

ETL

Data transformation processes 'Extraction, Transformation, Load'.

Technical and business rules are applied for the loading of information in the different databases.

Main Technologies used: Power Center, Talend.

Data Warehouse

Database with a standard structure guarantees the homogeneity of information, referential integrity, consistency and optimization of the space.

Data Mart

Information exploitation layer, that also differs in the following parts:

● Dimensional model, structured in a star schema or snowflake schema, grouping information into sets or universes.
● Closed reporting tools for complex dashboards or regulatory reporting.
● Open reporting tools to create new reports by the business user.

Main Technologies used: Tableau, Qlik View, Qlik Sense, MicroStrategy.

Big Data

Development of projects based on Big Data technologies, such as Hadoop, Spark, MongoDB ... Based on new definitions of architectures such as Lambda architecture.

Data is becoming a key element for businesses nowadays. Every business wants to improve their efficiency analizing the data they generate periodically, but due to the volume of said information, it needs to be treated with a series of non-traditional tools and techniques.

The solution to treat this volume of information is to use Lambda architecture. It provides an approach that allows to combine the treatment of data in real time and deferred, in a scalable and fault tolerant way.

A Lambda architecture is comprised of three principal layers:

The streaming layer (Spark Streaming + Kafka) allows us to retrieve data in real time, obtaining information and knowledge from them.

The batch processing layer allows to analize data originating from different sources of origin in a quick and scalable fashion.

The server layer: real time data as well as batch processed data are stored for later exploitation, using the different available techniques based on their utilization (Cassandra, Neo4J, MongoDB...).

These technologies allows for the use of not only non-relational databases but NoSQL databases as well, some that stand out among them are:

File Oriented
Graphs
Key - Value

This architecture allows creating prediction models (with tools such as Apache Mahout, Spark MLLib...) This is achieved through batch processing for the analysis of historic data stored on the servers and streaming data for real time predictions. The goal of these models is to provide added value to our business.

The benefits of Big Data are: