- Smart data company -

  • tinámica
  • EXPERT IN SMART DECISIONS
  • BIG DATA SOLUTIONS

About Us

WE OFFER TECHNOLOGICAL SOLUTIONS SPECIALIZED IN THE SMART DATA ENVIRONMENT

Experts in Smart Data

tinámica is a specialized company providing smart data technology solutions for the intelligent management of customer and operations information.We aim to provide the customer with the best technological solution, perfectly adapted to the quantity and certainty in the decisions to be taken and speed in them, with the highest success.
All our focus is oriented to data incorporation to the fast process of decision making with smart data and transformation in a data driven company.

This leads us to work on certain key factors to make our projects successful:

  • Quality data: In order for the information to be useful and to provide reliable results, it must be based on correct data at source and quality. We accompany customers in the process of acquiring and providing data with adequate quality and performance.
  • Intelligent business: Knowledge of the different business rules throughout the organization makes us able to access and analyze the data in depth, to allow the customer to select the solution that best fits their need.
  • Decisions based on valid data: At the same time, we aim to ensure that all processes contain smart data, and to provide the business user with all the solutions to accelerate and improve decision making.

Smart Data

We provide innovative technological solutions for smart management of customer and market information.

Customer Strategy

Business oriented. Everything starts with a business request, followed by an answer but many additional questions challenging the initial one, turning into a continuous Big Data discovery process.

Technology

We provide integral technological support, Big Data Technology and solutions to improve data information analysis and decision making.

Results

We have a retake rate from our customers over 85%, what clearly ensures our  customer satisfaction.  We commit a % of our salaries looking for excellence.

No borders

We have operations in
  • Europe
  • the Middle East
  • Latin America

Through our offices in Madrid, Dubai and Bogotá

Our values ​​make the difference

  • Leadership

    We believe that a leader is the person who can inspire and associate others with a dream. Our dream is sharing our customers success.

  • Passion

    Our team enjoys developing specific business solutions for each of our customers.

  • Professional growth

    We attract the best talent for our business. We are committed to the personal and professional development of our team.

  • Sustainability

    We promote sustainable management methods, which seek the efficiency of resources and time of our customers.

  • Teamwork

    We maintain a unique team attitude, aimed at achieving the results.

  • Customer orientation

    We are committed to our customers in obtaining business results, our relationships are long term and “win-win” type.

  • Integrity

    Personally and professionally, we want to maintain a trustful relation, so we are transparent, responsible and we act ethically.

  • Solidarity

    We believe in solidarity, shared work and the ability to help each other. That is why we donate one month of each year company profit dedicated to social causes.

Do you want to join Tinamica team?

If you are looking for work in a company...

  • Fun and passionate.
  • Dynamic and fast-growing.
  • High level co-workers and multiple profiles.
  • Where you can learn and grow continuously.
  • Leading edge technology.
  • Great customers to work with.
  • New professional challenges.

And what you offer is...

  • Passion for technology and data.
  • Team player.
  • Customer service orientation.
  • Professional and personal integrity.
  • University degree in Computer Science, Engineering, Mathematics or Physics.
  • Experience in Big Data technology and processes, as well as Advanced Analytics.
  • High level of English.

…send us your cv to rrhh@tinamica.com

Our Management Team

Integrated by great professionals and experts

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    Enrique Serrano Montes

    President & CEO

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    José Luis Molina Zamora

    Managing Partner

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    Raúl García Monclús

    Board member

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    Fernando José Corbacho Abelaira

    Board member

MANAGEMENT TEAM

A TEAM MANAGED BY THE BEST PROFESSIONALS AND EXPERTS

Enrique Serrano Montes
President & CEO

CEO at Tinamica since 2012, has been managing Telvent’s Telecommunication, Media and Technology Division for 2 years and was previously a partner of Matchmind and Director of Business and Technology Consulting, as well as Director of Communications and Human Resources. Member of the company Executive Committee.

He worked at Unisys (2 years) as Director of Change Management, KPMG (4 years) as Director of Management Services and PricewaterhouseCoopers (8 years) as Senior Manager, always focused on consulting areas.

His professional career started in the Stock Exchange of Lima in Peru as analyst and in the Zeta Group. He is Executive Coach and teaches in various business schools and at Carlos III University in Madrid. He holds a degree in Economics and Business Studies from the Universidad Autonoma de Madrid, a Master’s Degree in Business Organization from the Universidad Politecnica de Madrid and a PDG from IESE Business School. And since 2014 he is president of MBIT School.

José Luis Molina Zamora
Managing Partner

He led all the business sectors at Telvent Global Services until 2011, following the acquisition of Matchmind by Telvent. He was previously a partner of Matchmind, member of the Executive Committee and Director of different business divisions.

He was a founding Partner and Vice President of Product and Services at Globeflow, and after his acquisition by the British company Kewill Systems, he held the same position at Kewill Systems and was also a member of its Management Committee.
Between the years 1997 and 2000 at Cap Gemini Spain, was head of industry&Distribution consulting business, and then head of ERP implementation business in Spain. Previously, at the beginning of his professional career, he was a consultant at Accenture in the Telecommunications and Utilities sectors between 1993 and 1997.

He is an Agricultural Engineer from Universidad Politecnica de Madrid, with several postgraduate courses in business schools. He is president of the technology company Hispatec, specialized in ICT solutions for Agro sector.

Raúl García Monclús
Board member

He is member of the Steering Committee at Cognodata, leading the practice of Customer Strategy for financial services. From this position he has helped multinational financial institutions significantly improve their results, thanks to the definition of segmented business strategies and the development of systems, Customer intelligence and marketing, and business support tools.

Before taking the professional leap to Cognodata, he worked at The Boston Consulting Group on business strategy projects in the banking and telecommunications sectors. Previously, he developed his professional career in Argentina and England in the area of ​​Business Intelligence.
He holds an MBA from INSEAD and an IT Engineer from the U.P.C., occasionally collaborating with IE.

Fernando José Corbacho Abelaira
Board member

He holds the Operations Managing Partner position at Cognodata, and member of the Executive Committee, leading successfully projects of Customer Strategy, in which he has collaborated in the definition of customized marketing strategies by client segments, and in the design of campaign plans adapted to the business objectives.
He has more than fifteen years of experience in the area of ​​R & D & I in the Development of Intelligent Systems, and has made more than seventy publications in prestigious national and international journals, making presentations at various technological congresses of global scope.He holds a PhD in Computer Science and a Master’s Degree in Artificial Intelligence from the University of Southern California, as well as an Honorary Professor of Research at the Universidad Autonoma de Madrid.

SERVICES

TECHNOLOGICAL SOLUTIONS SPECIALIZED IN BIG DATA

tinámica is a niche company specialized only in SMART DATA technology.

We are experts in the data life cycle analysis, from the transactional systems to its consumption by the data scientist. Specialized in both Big Data Open Source technology processes, and the leading technologies of the most relevant software vendors. We are committed to the objectives, deadlines, costs and business results of our projects. We choose our teams based on knowledge and proven experience, and evaluate it beyond the certifications achieved. We are a company based on information management in an intelligent way, and we set an example with our internal processes. Tinamica works in 4 core areas of competence to execute smart data projects:
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Technology advice

We chose with the client the best fit technological solution, bringing the highest performance.
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Technological design

Definition, development and set up of processes and the Smart Data solution architecture.
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Development and Implementation

Ability to participate in the project in both architecture, technology and functional knowledge.
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Analytical Exploitation

We work on state-of-the-art analytical solutions with neural networks, Machine Learning and Deep Learning.

Smart Data Application Deployment

We are neutral in choosing the technology that best fits the customer, and we know the strengths of each technology to achieve the best integration.

  • Solution design and its architecture
  • Implementation / development of the solution
  • Specific adaptations
  • Solution optimization
  • Maintenance and evolution
  • Knowledge transfer

Big Data Architecture

Definition, design and operation of architecture, applications and distributed in-memory computing to evolve Big Data infrastructures.

  • Infrastructure, optimization and cost saving
  • BIG DATA Consolidation and Applications
  • Hadoop and Spark frames
  • NoSQL databases and In-memory computing
  • Advanced Analytics: Neural Networks, Deep Learning, Machine Learning, etc.

Big Data Discovery

Extracting value and patterns through the appropriate architecture, and analyzing data in real-time, multi-geography and multi-language.

  • Brand reputation analysis combining CRM, social networks and open data
  • Automatic collection of data from different sources and their integration into BI and BIG DATA
  • Building competition rankings
  • Integration of different processes

GEO Marketing Analytics

Use of geographic and territorial marketing data in advanced models, to discover behavioral patterns, in combination with local inputs, business and operational data, open data (meteorological, sociodemographic or other data).

  • Predictive models to discover new customer behaviors.
  • Simulations on potential customers demand, loyalty and cross-selling.
  • Cluster analysis to extract the best value.

Real Time Decision

Real-time optimization of business processes for better decision-making at all levels.

  • General purpose engine, automatically choosing the best option in real time, not being intrusive to operational applications
  • Systems learning from the process result and the predictive model

Data Acquisition and Quality

Extraction, transformation and data loading with additional data quality audit and data warehouse / Datamart / Data Lake model integrity services.

  • ETL Tools: PWC, DataStage, SSIS, ODI …
  • In-house data quality: Time series, statistics and distributions …
  • Infrastructure: OS, DB, cloud.
  • Big Data acquisition: Spark, Flume, Kafka

Big Data Governance

Data governance definition, process and organization policies in order to allow user control, identification and monitoring of the full data cycle.

  • Full traceability and data tracking
  • Control in new sources integration
  • Standardization of policies and protocols
  • Ensuring controlled access to data
  • Securitization of information and risk control

Big Data in Cloud

Smart data on demand services, fully scalable and pay-per-use to cover all areas, from the ETL or ELT layer, management and hosting of the Data Warehouse / Datamart / Data Lake to the Big Data platform.

  • ETL or ELT: design and development of cloud processes.
  • Data Warehouse / Datamart / Data Lake platform: on demand capacity.
  • BIG DATA Platform: Flexible and scalable platform for integration with client environments.
  • Analytical layer allowing the data exploitation from the Big Data point of view, as well as advanced analytics, allowing an intensive use of the new capabilities of analysis and data visualization

REFERENCES

DISCOVER SOME OF OUR SUCCESS CASES

Telecommunications and Technology

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Tunnel Curiosity. Development of unmanned multiple inspection vehicle in railway tunnels

Project co-financed by CDTI (Industrial Technological Development Center) and by the European Union through the Structural Funds for Regional Development.

The main objective of the project is developing an unmanned automated inspection vehicle, integrating data collection systems and information processing elements for rail tunnels, optimizing maintenance and consequently the safety of the railway infrastructure.

The specific objectives are to reduce maintenance, inspection time and decision time, by ensuring the safety of tunnels through reliable methodologies that can inspect and monitor critical elements from a single inspection platform.

The developments are oriented to long base railway tunnels, with large number of elements and high traffic density, although the possibility of extrapolating the developments to other objectives will be studied.

Visit the project website at http://tunnelcuriosity.es/

Participants

  • Alstom Transporte, S.A.
  • Vias y Construcciones, S.A.
  • Ferrovial Agroman, S.A.
  • Administrador de Infraestructuras Ferroviarias (ADIF)
  • Ingeniería Insitu, S.L.
  • Tinámica, S.L.

Big Data Analytics Solution to analyse customer service levels in Telecom Operator

Goals

  • Implementation of Big Data Analytics solution, which allows a better knowledge of the service level offered to the company’s customers.

Scope

  • Analysis of the initial situation and main challenges to be addressed. Establishment of metrics to evaluate the achievements.
  • Design and construction of technological and functional Big Data Analytics architecture, from multiple internal and external data sources with 360 client vision.
  • Building data ingestion processes in “streaming”.
  • Implementation of visualization tools and analytics, allowing an advanced and near-real time exploitation of the information.
  • Use cases and construction of some initial analytical models.
  • Support to the implementation of the architecture and solution defined.

Benefits

  • Better control in the service levels provided to the customer and identification of improvement areas.
  • Monitoring and continuous improvement process of the service provided, with customer loyalty and improved profitability.

Big Data Analytics architecture and solution for company in the agrifood technology solutions space

Goals

  • Definition and setup the Big Data Analytics solution, complementary to the company’s transactional management solution.
  • Collaboration in first projects to implement the analytical solution.

Scope

  • Joint definition of technological company business objectives.
  • Design and construction of Big Data Analytics technological and functional architecture in a private cloud, integrating internal transactional data and external data in the Data Lake of the defined solution.
  • Evaluation and selection of external data sources to be integrated.
  • Elaboration of use cases and description / estimation of business impacts to be achieved.
  • Implementation of the architecture and solution defined in the first use cases identified.
  • Construction of customer success stories.

Benefits

  • Identification and capture of new customers and market needs.
  • Loyalty of current customers.
  • Increased revenues and margins by the technology company.

Travel & Leisure

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Integration of external data sources in customer analytical environment to improve customer acquisition and loyalty in leisure / travel company

Goals

  • Greater customer knowledge or potential customer, and its environment.
  • Identification of growth opportunities and new segments.
  • New campaigns and improved commercial / marketing effectiveness.
  • Improvement of profitability by customer segment.

Scope

  • Analysis and selection of various external data sources to enrich customer analytics, depending on the potential to generate business benefits and the data quality and relevance.
  • Elaboration of use cases and description / estimation of business impacts to be achieved.
  • Functional and technical design in Big Data environment of external data integration, derived analytics, as well as commercial / marketing actions to be generated.
  • Construction of interfaces and data ingestion automated processes, analytical environment and campaigns automation.
  • Joint setup of the solutions, piloting and evaluation of results.
  • Continuous adjustment of generated models and actions.

Implementation of Sales Big Data solution in an air passenger transport company

Goals

  • Implementation of reporting and analytics solution with good response times and scalability, focused in customer sales data.

Scope

  • Reengineering of data models and architecture to a Big Data model, oriented to reporting and advanced analytics, with technical and functional scalability.
  • Design and construction of provisioning and data quality processes, all of it in streaming.
  • Implementation of infrastructure in the cloud to support the solution designed.
  • Construction of dashboards using advanced visualization tools.
  • Implementation of first analytical models and training to key users.
  • Joint implementation, piloting and evaluation of results.

Benefits

  • Elimination of bottlenecks in technical and functional scalability. Analysis of much wider temporal and geographical horizons.
  • Radical improvement of service levels to the business (commercial and marketing).
  • Improvement of analytical culture: better decisions based on data analysis.

Retail, Consumer Goods & Pharma

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Design, construction and implementation of an analytical and marketing platform for customers of a national retail distribution company

Goals

  • Improvement of customer knowledge: needs, satisfaction, environment.
  • Customer segmentation and effective marketing actions.
  • Knowledge and products and services offer adaptation to consumer preferences.
  • Improvement of profitability by customer segment.

Scope

  • Initial situation analysis, previous initiatives of individual identification of clients and loyalty, external sources of data.
    Conceptual design, functional and technical architecture of the solution.
  • Conceptual design, functional and technical architecture of the solution.
  • Selection of technological tools for data ingestion, storage, reports / visualization, advanced analytics and campaign automation.
  • Definition of data loading processes.
  • Design and construction of customers and sales Data Lake.
  • Design and construction of data transformation, debugging and loading processes in the Data Lake.
  • Definition and construction of reports and multi-channel visualization tools for data analysis, as well as its distribution mechanisms.
  • Design and construction of control panels.
  • Design and construction of campaigns, advanced reports and analytical models.
  • Elaboration and support to the implementation plan, pilot and setup.
  • Training in operation and tools to the business and marketing teams.
  • Post-implementation support, corrective and evolutive maintenance of the platform.

Benefits

  • Increased customer satisfaction levels and loyalty.
  • Commercial offer more adapted to the different customer segments, territories and seasons
  • Acceleration in commercial decision-making, based on better analytics.
  • Greater profitability in the different customer and product segments.
  • Analytical culture: decisions based on data analysis.

Banking & Insurance

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Data quality audit in a multinational financial entity

Goals

  • Update and data cleansing of the database of customers, products, services and promotions to increase the overall value of the portfolio by 10%.

Scope

  • Through the use of our methodology for audit of master data and synthetic variables, and with specialized tools, to achieve:
    • Table Integrity.
    • Integrity between tables.
    • Statistics at column level.
    • Statistics at table level.
    • Analysis of time series.
  • Relevance and correlation of variables.
  • Modeling.
  • Results measurement.
  • Automation of code generation.
  • Plan for correction of detected inconsistencies.

Benefits

  • Use of indicators to ensure activity control in real time, fully linked to the business objectives.
  • Acceleration in commercial decision making.
  • Early detection of deviations from budget targets or reported by other corporate systems.

Design and implementation of Solvency II compliance processes in a national insurance company

Goals

  • Definition and design of information capture processes from transactional systems, allowing the assets, liabilities and capital valuation, supervision / audit and transparency.

Scope

  • Functional and technological analysis of source information systems.
  • Design of data provisioning processes.
  • Construction and process testing.
  • Operation automation and supervision.
  • Quality control and documentation of the processes implemented.
  • Training to user areas.

Benefits

  • Regulatory compliance with legal requirements in the established deadlines.
  • Data quality and better risks control.
  • Efficient solution, robust and maintainable from a technological point of view.

Utilities / Energy

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Big Data transformation model in multi-national energy company

Goals

  • Design and implementation of Big Data architecture to maximize the possibilities of new technology and approach.
  • Efficiency in resources and deadlines, in Big Data projects and solutions.

Scope

  • Understanding business needs and priorities.
  • Design of new Big Data architecture, both technically and functionally.
  • Organizational and governance model.
  • Demand management and service delivery model.
  • Transformation program.
  • Piloting and implementation of best practices.
  • Innovation and introduction of new technologies.
  • Metrics and results tracking.

Benefits

  • Best practices in Big Data solutions with demonstration effect.
  • Less time to provide solutions. Deadlines.
  • Self-service capabilities, visualization and advanced analytics.
  • Functional and technical scalability of solutions.
  • Greater business user satisfaction.

BLOG

LAST NEWS AND SOME OF THE BEST ARTICLES ABOUT BIG DATA.

El sector bancario es uno de los más avanzados en la integración y calidad del dato. Las numerosas fusiones y adquisiciones de los últimos años y las exigencias regulatorias del mercado han situado a este sector a la cabeza en cuanto a mecanismos para asegurar la trazabilidad del dato. Estar a la vanguardia les ha permitido poner en marcha nuevas técnicas de marketing exitosas y se ha conseguido un incremento de los ingresos en la cuenta de resultados.

Sin duda alguna el BIG Data ya está aquí y ha venido para quedarse, y nadie duda que con el "internet de las cosas" habrá una explosión de la información y una ingente cantidad de datos disponibles. Pero también habrá una gran cantidad de “basura” de datos que se irá generando al mismo ritmo puesto que hablamos de datos que tienen validez en el momento de su creación y una vida muy corta.

La creciente cantidad de información que emiten los usuarios hoy en día ha supuesto para las empresas una imperiosa necesidad de monitorizar y medir todo aquello que sea susceptible de ser controlado legalmente. El uso de las redes sociales y la convivencia 24/7 de los usuarios con los smartphones, supone un generador ingente de datos e información de la actividad del usuario que puede y debe ser aprovechada por las compañías.

Press releases

DISCOVER TINAMICA ACTIVITY IN THE MASS MEDIA

Leer Más
14 febrero 2016
Tinámica chosen among the 30 technological companies that will represent Spain
Leer Más
28 noviembre 2016
Present on Spanish TV program "Here there are jobs"
Leer Más
16 octubre 2016
Tinamica in the SAS Forum Spain 2016
Leer Más
23 septiembre 2016
Big Data, a partner against the dark Internet
Leer Más
22 septiembre 2016
The Agrifood sector also relies on Big Data
Leer Más
12 septiembre 2016
Data Economy: the revolution of data
Leer Más
2 septiembre 2016
The company that realized about data value
Leer Más
20 julio 2016
Big Data optimizes company performance metering, according to Tinamica
Leer Más
19 julio 2016
Big Data allows the energy sector saving up to 70%
Leer Más
7 agosto 2016
The three types of Big Data
Leer Más
11 julio 2016
Big Data and Agrifood sector: a partnership with future
Leer Más
22 junio 2016
What are missing the political parties for not using Big Data in their campaigns?
Leer Más
13 junio 2016
Big Data replaces Octopus Paul
Leer Más
12 junio 2016
Interview to Enrique Serrano in "El Diario Montanes"
Leer Más
18 abril 2016
7 requirements to implement Big Data
Leer Más
30 abril 2016
Big data allows companies to do things better
Leer Más
12 marzo 2016
"There are terrorist attacks that have been avoided thanks to Big Data"
Leer Más
13 abril 2016
Seven steps to guarantee a Big Data project
Leer Más
28 marzo 2016
Tinamica, specialist in Big Data management
Leer Más
1 marzo 2016
Tinamica bets for internationalization
Leer Más
11 marzo 2016
Whoever is doing really well with the use of the data, prefers not to tell it
Leer Más
2 marzo 2016
Tinamica starts exporting Big Data technology to the Middle East
Leer Más
30 diciembre 2015
"Spain has pioneered Big Data adoption"
Leer Más
20 enero 2016
Why is "big data" an ally for your company
Leer Más
15 enero 2016
Are you a potentially dangerous citizen? Big data as an ally of the Security Bodies
Leer Más
20 octubre 2015
Half of the banks will disappear in Spain
Leer Más
21 diciembre 2015
Interview to Enrique Serrano in ITweb.tv
Leer Más
18 diciembre 2015
Does the social networks Big Data predict better than polls who will win the election?
Leer Más
7 septiembre 2015
"Big Data allows the hotels growing their business"
Leer Más
24 septiembre 2015
A next mandatory step after Big Data
Leer Más
8 septiembre 2015
Benefits from Big Data for the SME
Leer Más
23 junio 2015
Big Data and Business Intelligence (Try IT! 13/20)
Leer Más
24 abril 2015
How to tackle a Big Data project?
Leer Más
22 junio 2015
Big Data offers up to 50% improvements in customer satisfaction in omnichannel contacts
Leer Más
15 enero 2015
"If it does not create value, the 'big data' can become a 'big problem'"
Leer Más
13 abril 2015
See how it works the "data tailor" of Vodafone, BBVA and Endesa

CONTACT US

IF YOU HAVE ANY QUESTIONS OR LOOK FOR MORE INFORMATION, CONTACT US.

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Subject

Message

tinámica Spain

Paseo de la Castellana, 135 – 28046 Madrid (España)

+34 91 787 96 15

tinámica Colombia

Calle 93ª # 13-24, Piso 5 Edificio QBO – Bogotá DC – Colombia

+5731341671 21

tinámica United Arab Emirates

Horizon Tower 4102, Dubai Marina, Sheik Zayed Road – 454294 Dubai

@tinamicabigdata

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