DIGITAL TRANSFORMATION
Big Data Solutions
Solutions
Big Data Strategy
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Big Data Strategy
Designing a Big Data strategy is key to ensuring the success of the digital transformation that a company must undertake to adapt to the new demands and needs of customers.
Therefore it is essential
Leathership
The design of a horizontal strategy in the organization
The internal cultural change
Our team of expert consultants in Big Data helps you define the Roadmap of your Big Data strategy based on an initial diagnosis that will take into account the technological maturity of your company and the business aspects to improve.
In order to fully understand the needs and objectives of the company, the collaborative work of both teams will be essential.
We must become
Big Data diagnosis
PHASE 1
Company knowledge
Joint definition of what needs to be improved in the company
PHASE 2
Diagnostic
Assessment of the current situation and technical requirements
PHASE 3
Road Map
Roadmap and execution of the company’s big data strategy
Data Arquitecture
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Data architecture
To transform your company’s data into business insights and intelligence, the first technical challenge is to have the architecture and technological tools necessary to support an entire Big Data ecosystem.
The most common problems in data science are:
Quantity
Volume
Type of data
Being able to process all this information in reduced times requires distributed systems. The design of the Big Data architecture is key to implement the systems and technologies necessary to be able to distribute all that information.
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Architecture of ad hoc data
From BusinessGoOn we offer Ad-hoc Big Data architecture services for companies, designing the structure and the choice of tools and technological components that support the Big Data projects proposed according to the needs of the company.
Given the existence of different options when configuring a Big Data Architecture, we have experts with knowledge in different solutions for custom design and development.
Depending on the characteristics of your company, the level of security required, the processing capacity and storage needed, at BusinessGoOn we offer you the development of your Big Data projects …
Either through cloud solutions (IaaS, PaaS, SaaS), on-premise (in your own offices) or hybrid, with the support of our technology partners:
- Cloud supported platform
- We work with trusted partners: Amazon Web Services, Microsoft Azure or Google Cloud Platform.
- Hadoop solutions specialists
- Through partners such as Cloudera and HortonWorks among others.
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Cloud, on-premise and hybrid infrastructure
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Flexibility and scalability.
To allow the progressive growth of your company and its adoption of Big Data projects, any data platform has to comply with the premises of flexibility and scalability.
In Big Data environments, the platforms are highly flexible, adapting according to data storage and processing needs, as well as incorporating new capabilities (IoT platforms, tools, APIs, new data sources, etc.).
In this sense, it is crucial that from the very design phase of the data architecture, the possibilities of scalability of the same are foreseen, for the productivization of the models and processes to be developed.
This also translates into reduced implementation, development and maintenance costs.
Data Engineering
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Data engineering
Data veracity, correct decisions
Once the architecture that will support the Big Data Ecosystem has been designed, the next step is to ingest the data into the data lake, as a single repository of all the data related to your company and its environment, regardless of its nature, typology or volume.
Big Data
It allows the agile incorporation and dynamic processing of new data sources without the need for architecture development
Data engineering
It establishes the standards that any company needs to dispose of its data in a unified, clean and accessible way, responding to the requirements of the company
Its importance is crucial
And since it is the phase in which the data is prepared so that in the later phase, the advanced analytics, the models are executed on precise data, which can provide truthful business conclusions. If the data is not reliable, the business decisions will not be correct
Information processing
Data engineering services for information processing
At BusinessGoOn we offer all our own data engineering services, from data modeling, to migration and automation of data ingests through scheduled workflows.
Modeling and organizing data
Data distribution and replication scheme for their security.
Organization of data for agile access.
Data quality
Profiling and enrichment of the variables.
Definition of data quality processes.
Cleaning and standardization processes
Generation of variables, attributes and indicators directly from DATA LAKE.
Definition of the data transformations, necessary after the extraction of its original internal and external sources.
Data ingestion process (batch and streaming)
Integration and treatment of structured, semi-structured and unstructured data. Definition of strategy and data ingestion roadmap, with appropriate latency times. According to the type of data that each company has.
Process automation
Design of automatic data cleaning and normalization processes.
Framework for data integration automation.
Data Analytics
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Data Analytics
Generation of new business sources
The data allows you to have a deeper knowledge of your client, and this makes it possible, together with the application of Machine Learning and Deep Learning techniques, to be able to customize your products or services so that your company better adapts to the needs of the consumer .
Therefore, by knowing your client you can improve the effectiveness of campaigns, improve cross-selling ratios, boost up-selling, etc.
Improved operational efficiency
Thanks to the correct storage and provisioning of data in real time, together with technologies such as IoT, we are able to have a unified knowledge of the processes, a production chain or a machine.
A comprehensive view of the production environment will allow you to anticipate a possible breakdown or anomaly, as well as improve maintenance cycles, which translates into operational efficiency.
Prevention and prediction of fraud and risk
With the ability to analyze not just a sample, but the entire data set, we are more efficient at detecting anomalies.
Likewise, the option of integrating new data sources, which complement the information of your company and generate relationships that you did not know, such as official statistics, social networks, makes it possible to detect patterns of behavior and determine possible fraudulent or irregular cases, which It will allow you to mitigate future costs.
Data Visualization
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Data Visualization
Translation enters the technical and business layer
One of the biggest challenges posed by Big Data is knowing how to make decisions in light of the results produced by the models and algorithms.
The data visualization area, almost intrinsic in any Big Data project, has the mission of clearly and graphically showing the results obtained from a project, mainly through dashboards; It includes different types of graphs, such as heat maps, maps with geolocated data or with movement flows, where it seeks to answer all the questions posed at the beginning of the project and in this way turn the insights into actions.
The data visualization tools allow to represent any type of information in a visual and simple way.
At BusinessGoOn we work with tools such as Tableau, CARTO, D3, leaflet, R libraries, among many others to be able to graphically represent the projects carried out.
Internet of Things
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Internet of things
The increasing need for companies to digitize to face an increasingly changing market and increasingly demanding customers has led companies to populate their processes with multiple machines (sensors, meters, GPS devices, computers, etc. .) in order to have an end-to-end view of your business from a process point of view.
New challenges
The inclusion of all these devices in companies is posing new challenges in terms of the storage, treatment and analysis of all this data, in multiple formats, now available to organizations.
Advanced Analysis
It is thanks to Big Data and the use of Advanced Analysis techniques, that for the first time companies can have a unified vision of their processes, understanding their operation, their status and the environment.
Data Gobernance
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Data gobernance
Transforming a company to a data-oriented one is not an easy task, it means having a very clear strategy at the managerial level that allows prioritizing Big Data use cases that respond to business needs.
Likewise, a strict definition of policies and regulations is required regarding the use of data, which is called data governance.
Data governance establishes a reference framework, necessary to maximize the value of the information available across the entire organization through the definition of policies, procedures and roles that facilitate effective management of the data life cycle.
From BusinessGoOn, we offer our clients solutions to guarantee the integrity of the data and its efficient management.
Practical applications of Big Data
Generation sources of income
Detection of high value customers for the company
360º vision of the client
Define the optimal product / service portfolio for each segment
Sales prediction
Dynamic prices
Increase and improve cross-selling ratios and boost up-selling
Create personalized recommendations
Attract new customers with Lead Scoring
Improving operational efficiency
Office datafication
Machine monitoring and maintenance
Stock management in real time
Route optimization in logistics transport
Prevention and prediction of fraud and risk
Customer churn prediction
Detection of fraud and other anomalies
Prevention of delinquency or non-payment of clients
Anti-corruption monitoring of activities
References
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Do not hesitate to contact us for any questions. We will be delighted to assist you!