Solutions

Data Platform and Analytics Solutions

Building optimal data analytics platform and providing analytics support according to customer needs, issues, and circumstances

Overview

These solutions support the building of data platform and data analytics using AWS in line with diverse data types, storage environments, and demands for utilization.
They serve a wide variety of demands, from the building of environments and analytics supports in relatively small scale to data warehouse (DWH), machine learning, and a range of statistical analyses in medium- to large-scale.

Overview of Solutions

Anticipated Issues

With these solutions, you can solve a variety of issues relating to data platform and data analytics as follows.

Data Platform and Data Management

  • Data is scattered throughout the organization, and thus, is not readily available for analysis.
  • A record of activities on the web and data obtained from outside information vendors are not archived.
  • Tools that can be used by those other than data scientists are not available.
  • Data is unfit for analysis as its quality is poor due to problems such as loss of data and incompatible data types.
  • Data dictionary is missing, making it difficult to determine the meaning or source of an item.
  • Analytic environments, such as Python/R, are not available for use as security rules are not updated.

Data Analysis and Human Resources Development

  • The organization lacks human resources who can present the perspectives and scenarios for marketing analysis based on business strategies.
  • A higher priority is given to discussions about methods, such as BI tool and MA tool, and operational issues to be solved are not defined.
  • The organization lacks a scheme whereby what data suggests is well reflected in business activities.
  • The organization lacks data scientists capable of sophisticated analysis.
  • Data is not used for extracting suggestions or future projections due to a strong awareness that data is a record or an accumulation of past information.

Features

Realizing flexible and highly scalable data analytics platform

The solution allows for the extraction of data from a variety of data sources, such as on-premise environments and SaaS applications. Users can achieve a high level of data durability and protection by storing extracted data in a data lake on Amazon S3. In addition, the analytics platform is scalable into a variety of forms, for example, from a small-scale analytics platform using Amazon Athena or Amazon Quicksight to Amazon Redshift (data warehouse), Amazon SageMaker (machine learning), and OpenSearch (full-text search) depending on respective needs.

Realizing data governance from both offense and defense perspectives

We provide both defensive and offensive data governance, including secure access to data using AWS Lake Formation and preventing data quality degradation using AWS Glue Data Quality on the defensive side, and converting data into a catalogue using Amazon DataZone on the offensive side. We also provide a broad range of supports, drawing on our expertise in advanced security measures and technologies we have accumulated through our solid track record of introducing the system to many financial institutions. These supports span widely from the implementation of data platform to its operation.

Supporting diverse industries/sectors and analysis phases

We can support the building of data platform and data analytics in various industries and sectors by leveraging our in-depth technical capabilities cultivated over many years of our experience in the financial sector and our mathematical knowledge in the quants field which has a high affinity with AI. In data analysis, our data engineers and data scientists support the realization of effective data analysis in each data analysis phase, from problem setting to modeling and implementation.

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