Data management: In-depth guide [2018 update]

Leading tech companies such as EMC predict exponential data growth with available data doubling every 2 years.

With this increase in volume comes an increase in need to determine a way to manage it. Subsequently a wealth of data management techniques, tools, vendors, careers, have emerged to support this need.

To better help your business achieve effective data management, it is necessary to first understand what exactly is data management and how it can become beneficial for your organization.

What is Data Management?

Data has a lifecycle that requires careful management from the day it is created until the day it is no longer in use. By managing this data properly, the risks are greatly decreased and the usability and quality of the data is greatly increased. Ultimately these two things together lead to a better and more profitable business no matter the industry or topic.

Some of the biggest focus points in data management include:

Data quality: Share

Understanding ETL Tools

ETL, or Extract, Transform, Load is the process of integrating data from multiple applications (systems), converting them to a single format or structure and then loading the data into the target, often a data warehouse. This process is essential for data analysis, business intelligence, and other related tasks – particularly in businesses with a wide range of data sources and formats to consider.

Selecting the right tool to do so is integral to ensuring the success of not only the specific action, but also for the overall goals and efforts of the business. To learn more about ETL and get a better understanding of how businesses use it, visit our ETL blog post.

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Integrating IoT Analytics for a Smarter Future

By 2020, it is expected that there will be between 20 and 30 million IoT units in the marketplace, according to a study conducted by Gartner. With this much data being collected, the need for a way to analyze it grows exponentially. Many of the enterprise applications for IoT analytics, such as in manufacturing, finance, telecom, healthcare, and others have unlimited potential when data is managed and analyzed correctly.

To meet this need, IoT analytics has emerged as the broader category of uses and applications designed to help analyze the data obtained by IoT sensors. Once this data has been properly analyzed it can then be used to help make better, data-driven decisions for organizations that are in search of a competitive edge.

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Manufacturing analytics: $6T opportunity

There has been sustained excitement about IOT and the data capabilities it will bring to industry. In 2013, McKinsey&Company had predicted that IOT would bring $3-6T economic impact in 2025.

With margins getting smaller and competition getting more intense, manufacturing companies are getting smarter about how they can become more productive in order to become more profitable. Manufacturing analytics is one of the most effective ways to do so.

Sometimes called the 4th industrial revolution, manufacturing analytics analyze the historical performance data of machines in order to forecast their future; and their failure. And with technology and the environment to support it evolving rapidly, there has never been a better time to get started. Read more

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