Science and Tech

Data management tools and how you can think about the technology

Data management is a rather broad and unclear concept. According to the Global Data Management Community, data management refers to the development of architectures, policies, practices as well as procedures to control the data life cycle. However, when data management is mentioned, it is often categorized in five possibilities.

  1. The definition of data management

Data management is a rather broad and unclear concept. According to the Global Data Management Community, data management refers to the development of architectures, policies, practices as well as procedures to control the data life cycle. However, when data management is mentioned, it is often categorized in five possibilities.

Cloud data management is the process of integrating data from the ecosystem of a company of cloud apps. The main point of cloud data management is that all data storage and processing will occur in a storage based on cloud.

ETL and data integration means loading data from a wide variety of sources into a data warehouse, transforming and summarizing them into a format which can be used for deeper analysis.

Master data management is a method for controlling important organizational data, including customers, accounts and parties engaged with the business transactions in a standardized manner that avoids redundancy throughout the company.

Reference data management defines the values that can be utilized by other data fields like postal codes, country lists, regions cities or product serial numbers. Reference data can be made by the company or offered by other parties.

Data analytics and visualization means processing chosen data from sources and warehouses, carrying out advanced data analytics and letting analysts or data scientists take advantage of it to generate results.

Because of the huge amount of data nowadays, high-quality tools are really important to achieve data management best practices. Companies are using the below data management tools from the above types to control and automate the data management process.

Cloud Data Management tools can be built on the cloud and for the cloud, these tools link with different data sources through webhooks, API’s or direct database connections.

ETL tools will support companies to load data from a range of sources, define complicated transformations of the data, check the data pipeline and load data regularly to a target database or a data warehouse.

Data Transformation tools deal with transforming raw data into clean data and analyze data when it transfers from personal data sources to an analytics warehouse or in the analytics warehouse, at the point of analysis.

Master Data Management tools assist in visualizing complicated sets of master data throughout the company and facilitating data stewardship as well as maintenance of reference data.

Reference Data Management tools are usually offered as a component of master data management suites, which will define business processes around reference data, and support stakeholders to populate reference data to control it regularly.

The last tool is data visualization and data analytics tools by which organizations can discover, analyze and visualize big data sets then generate reports to extract insights and make right decisions for the business.

Now let’s take a look at some great tools in the category of cloud data management so that you can learn more about this tool and have a chance to understand more before choosing the best data management tool for your demands.

Because storage and bandwidth have become much less expensive, more and more off-premise solutions for data warehousing and managing have become available. Organizations with huge amounts of data to deal with and analyze now can store and handle their data totally in the cloud. In spite of the fact that the area has been pioneered by such giants as Amazon and Google for such a long time, many companies of smaller sizes now also provide their clients with tools according to every specific need.

  1. Panoply

Panoply provides a cloud-native automated data warehouse by which users can integrate and deal with all of their business data easily. Some main features offered by Panoply include large choice of native data connectors for easy data ingestion, intuitive management dashboard to remove the guesswork from data management tasks. Moreover, automated data ingestion and preprocessing help free up IT resources. There are also connections to common data visualization and analysis suites including Tableau and Chartio. The cost for this cloud data management solution is just over 300 dollars a month.

  1. Amazon Web Services

Amazon Web Services provides a suite of tools which can be used for a good-quality cloud data management stack. The main services include Amazon S3 for current and immediate storage, Amazon Glacier for long-term backup and storage, Amazon Web Services for setting up data catalogs to define, search and query your data, Amazon Redshift for data warehousing or Amazon Quicksight for dashboard establishment and data visualization. Each of the service will be charged independently so that you will only need to pay for what you use. This is a very convenient price for businesses of small size.

  1. Microsoft Azure

The Azure platform from Microsoft offers a lot of different ways to build a data management system based on clouds, as well as analytics tools which can be utilized on your Azure data. Similar to Amazon Web Services, this tool will enable multiple database or data warehouse styles with a wide variety of tools to control them. The major services include standard SQL databases and virtual machine SQL servers, blob storage, NoSQL table storage options, private cloud deployments and quick integration with Panoply for ELT or ETL services. There is also a newly added service named Azure Data Explorer, which will enable real-time analysis for large streaming data while there is no need to preprocess.

  1. Google Cloud

Similar to Amazon, the cloud platform from Google provides a lot of tools for data management based on cloud, as well as a workflow manager that can be taken advantage to connect different elements together. The main Google Cloud elements include Big Query for data storage, Cloud Big Table for NoSQL data storage, Big Query analytics for SQL queries, Cloud Datalab for data science based on code, connections to common Business Intelligence tools such as Tableau, Looker and so on. The price for Google cloud data management also depends on your usage.

 

 

Leave a Response