Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Five Key Benefits of Retiring Legacy Applications to the Data Lake
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Warehousing > Five Key Benefits of Retiring Legacy Applications to the Data Lake
AnalyticsBig DataData ManagementData WarehousingExclusive

Five Key Benefits of Retiring Legacy Applications to the Data Lake

Sean Martin
Sean Martin
4 Min Read
SHARE

With its promise to transform data management and analytics by providing access to all data across the enterprise, the data lake is quickly becoming more than just an industry buzzword. Unlike traditional data warehouses, which have frequently resulted in lengthy implementation time, inflexibility and high costs, the data lake accommodates any type of data and stores it cheaply, in very large volumes, on commodity hardware.

With its promise to transform data management and analytics by providing access to all data across the enterprise, the data lake is quickly becoming more than just an industry buzzword. Unlike traditional data warehouses, which have frequently resulted in lengthy implementation time, inflexibility and high costs, the data lake accommodates any type of data and stores it cheaply, in very large volumes, on commodity hardware.

Business users and IT professionals alike have long been tasked with the challenge of preserving and collecting data from outdated computing systems, often referred to as legacy applications. Legacy applications that have exceeded their useful life can be expensive to maintain, often requiring dated versions of software and hardware to maintain support. Despite these challenges to the enterprise, legacy applications also contain valuable data that needs to be retained for business or compliance purposes.

More Read

big data seo
The Dual Utilization of Big Data In SEO And UX
Research Uncovers Keys to Using Predictive Analytics
Why Old Media Can’t Deny New Media
What Are the Ethical Implications of Using AI in Advertising
Seven Misconceptions about Data Quality

Here are five key benefits of retiring applications to the Data Lake:

1. Data Preservation

By mapping the data to a business-friendly conceptual model, the data lake can preserve institutional knowledge of the meaning of data in legacy applications. The model is a high-level domain representation more easily understood by business users, eliminating the need for specialized application skills down the road.

2. Cost Efficiency 

The emergence of the data lake brought promise of the ability to collect vast amounts of data in its native, untransformed format at a very low cost. The data lake provides easy-to-use mapping and ETL tools to migrate data from legacy applications to a low-cost, Hadoop (HDFS) storage environment.

3. Self-Service Workflow

With a data lake, end-users are provided critical capabilities including data cataloging, data meaning, data provenance and self-service data analytics via available data sets.

4. Convenient Accessibility

The availability of data stored in the data lake is virtually instantaneous, providing on-demand access to high-performing, in-memory query search and analytics capabilities across any legacy data set. As a result, the analytics capabilities, in many cases, have far exceeded those of the legacy application.

5. Enhanced Value

A vast majority of large organizations have realized that the information captured in the normal course of business has enormous strategic and competitive value. Though the data lake, data value is enhanced by making it easy to combine and analyze with other data sets. As a result, end users can combine and ask questions of the data – something not previously possible.

As more businesses begin to take notice of the value of big data, data lakes can serve as an ideal complement to low-cost, commodity cloud infrastructure for providing a retirement home for their legacy application data sets. By providing data that is more accessible to business users and easy to combine with other data sets, data lakes can also provide a return on investment that goes beyond just saving costs.

 

Share This Article
Facebook Pinterest LinkedIn
Share
BySean Martin
Follow:
Sean Martin has been on the leading edge of Internet technology innovation since the early nineties. His greatest strength has been the identification and pioneering of next generation software & networking technologies and techniques. Prior to founding Cambridge Semantics, the leading provider of smart data solutions driven by semantic web technology, he spent fifteen years with IBM Corporation where he was a founder and the technology visionary for the IBM Advanced Internet Technology group.He is a native of South Africa, has lived for extended periods in London, England and Edinburgh, Scotland, but now makes his home in Boston, Mass.

Follow us on Facebook

Latest News

data analytics and truck accident claims
How Data Analytics Reduces Truck Accidents and Speeds Up Claims
Analytics Big Data Exclusive
predictive analytics for interior designers
Interior Designers Boost Profits with Predictive Analytics
Analytics Exclusive Predictive Analytics
big data and cybercrime
Stopping Lateral Movement in a Data-Heavy, Edge-First World
Big Data Exclusive
AI and data mining
What the Rise of AI Web Scrapers Means for Data Teams
Artificial Intelligence Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Image
AnalyticsBig DataBusiness IntelligenceData MiningExclusiveInside CompaniesModelingPredictive Analytics

Amazon: Using Big Data Analytics to Read Your Mind

6 Min Read
big data helps religion
Big DataExclusive

What Does Big Data Say About Religion?

5 Min Read

The Rise of the Columnar Database

5 Min Read
big data and net neutrality
Big DataExclusive

How Big Data And Net Neutrality Repeal Impact Each Other

8 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?