As the world is gradually becoming more dependent on data, the services, tools and infrastructure are all the more important for businesses in every sector. Data management has become a fundamental business concern, and especially for businesses that are going through a digital transformation. A survey from Tech Pro Research showed that 70 percent of organisations already have a digital transformation strategy or are developing one. Solutions for the various data management processes need to be carefully considered. Extensive planning and taking discussions on the best possible strategies with the different teams and external consultation should be a priority.
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What is data management?
Data management can be defined in many ways. Usually the term refers to the practices, techniques and tools that allow access and delivery through different fields and data structures in an organisation. Data management approaches are varied and may be categorised in the following:
- Cloud data management. The storage and processing of data through a cloud-based system of applications.
- Master data management. The techniques for managing organisational data in a standardised approach that minimises inefficiency.
- Extraction, Transform, Load (ETL). The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse.
- Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated.
- Data analytics and visualisation. This involves the processing of selecting data from data warehouses, data analytics and presentation in dashboards and visualisations.
- Reference data management. This is the defining of values that can be used in different data fields, such as postal codes or serial numbers.
Amazon Web Services
A cloud-based solution with a wide range of tools from a giant in cloud services. The main services include Amazon Glacier for storage and backup over long-term periods, and Amazon S3 for storage on a temporary or immediate basis. Redshift is the product for data warehousing, and Athena provides SQL data analytics. AWS Glue helps users to build data catalogues, and Quicksight provides data visualisation and dashboard construction. The services from AWS can be catered to meet the needs of each business user.
SharePoint from Microsoft is a flexible solution that businesses can use for data storage and retrieval. Content can be shared throughout an organisation, and accessed through an intranet URL. Staff members can access and upload various forms of content, and management can share information across the company through news feeds. Another option is SharePoint Online, which is a secure cloud solution. This allows the storage of up to 1TB of data, and it is often included in the Microsoft 365 package. SharePoint is a flexible and accessible data management solution, which makes it particularly suitable for small businesses.
This is a master data management tool that cleans, matches and standardises data without coding. The tool assigns the role of ‘data stewards’ in an organisation to manage master data. Data stewards can be managed internally, but the solution enforces business processes across the organisation. Profisee notices changes in data and assigns events within the systems. For companies that operate around the world, master data is federated with bi-directional integration in real time. Custom applications can also be integrated.
A data warehouse that is automated and cloud native, Panoply helps in the integration and management of organisational data. It has useful features, such as an in-browser SQL editor for queries and data analysis, various data connectors for easy data ingestion, and automated data prepossessing and ingestion. Panoply also has an intuitive dashboard for management and budgeting, and the automated maintenance and scaling of multi-node databases.
Dataform is a data transformation platform that is based on SQL. It is used for managing processes in a data cloud warehouse. SQL workflows can be written by teams as part of a collaborative IDE. Dataform enables the creation of a central repository for defining data throughout an organisation, as well as discovering datasets and documenting data in a catalogue. The platform allows data quality tests to be written with alerts, and schedules that ensure data is kept current.
The Azure platform has a variety of tools for setting up data management systems, and analytics tools that can be applied to the stored data. There are different management tools available, as well as a range of warehouse and database options. Databases can be SQL or Blob storage for unstructured object data. Azure Data Explorer (ADX) enables the analysis of large streaming data in real time, and without preprocessing. Private cloud deployments are also possible with Azure.
Airflow is a new open-source data infrastructure tool that was originally developed for Airbnb. It allows users to organise, monitor and schedule ETL processes through the use of Python.
It makes use of directed acyclic graphs (DAGs) for spreading employee tasks across the scheduler. This escapes the need to define relationships in the workflow. Airflow is especially useful for web-based UI, and it can be used for editing directed acyclic graphs (DAGs). The tool is both flexible and scalable.
In the modern, data-driven business world, enterprises need to keep up with every tech-related development in order to keep up with the competition. Developing an effective data management strategy that will allow the business to scale should be a priority.