The primary benefits of a data lake are speed, scalability and efficiency. Data lakes are one of the most important tools enterprise companies have to get the most value out of their data. Because of their simplicity, data lakes are also much more easily scalable than structured data storage. In order to take advantage of machine learning and predictive analytics, organizations need to be able to store and access as much data as possible.ĭata lakes, such as an Azure data lake, provide the ideal environment for a growing organization to store data that it knows may be useful, without the delay, effort and expense of cleansing and organizing data in advance. Historical sales and marketing data can be used to predict future performance, and as more data becomes available - along with more sophisticated machine learning and big data analytics tools - those predictions become more accurate. Machine learning and other advanced analytics provide a self-service option for administrators to glean insights from an organization’s historical data and use it to predict future outcomes, whether that means protecting the company from external threats to their networks, finding ways to streamline and optimize workloads, or keeping networks up and running. Ensure your organization’s data governance, security and privacy standards are maintained.Ĭompanies are constantly being told that data is their most valuable asset. Select the best server architecture for your needs.Ħ. Develop an action plan and assign ownership of the project.Ĥ. Gather relevant stakeholders and decide on your goals.Ģ. Most resources that describe best practices for developing a data lake are describing best practices for any major technology undertaking in a large organization:ġ. In other words, a data lake could be the data itself, and the data lake platform the servers, other equipment, hardware and software used to operate and maintain it. While there doesn’t seem to be a widely accepted definition of “data lake platform,” ancillary services are required to manage the servers, provide security and storage services and make the data available for extraction and use. In and of itself, a data lake is a collection of data stored in its native format on a server, either on-premises or in the cloud.
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