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data analytics strategy
  • Data Management
  • Data Analytics
   

Data Is The New Water: Why Investing In Data Pipeline Is A Must For Businesses

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Data is being increasingly seen as the foundation of the new industry and economy. But data alone cannot be used to drive business outcomes. Data must be sewn together using strong analytics frameworks, and only such a robust framework will help to close the gaps between data, insights, and business outcome.

The key to succeeding with a data analytics strategy is to invest in a strong data analytics pipeline.

Build phenomenal data pipelines

Thriving with your data starts with a solid strategy, and our data analytics consulting experts are here to help

By investing in strong data analytics pipelines, companies can transform data into active intelligence that will help to drive better decisions and to streamline the bottom-line impact, while ensuring data quality and data integrity - while ensuring data cataloging, metadata management and lineage for data governance.

lineage for data governance

According to the IDC CXO Survey done in Q1 2020, 87% of CXOs said that becoming a more intelligent enterprise is their priority for the next five years. (Source: IDC CXO Survey, Q1 2020)

Even as economic indicators have taken a hit as a result of pandemic induced business recession, 25% of respondents to the IDC and Qlik poll still expect short-term spending to continue to increase on solutions that manage and analyze data.

Another 26% said that short-term spending would stay the same as compared to their Budget while the rest expect a decline.

data pipeline

Q. In the last 12-18 months, has your organization done any of the following?

data management analytics

Over 60% of organizations said that they are experiencing significant challenges in:

  •  Investing in the right technology to create data
  • Assessing the value of data
  • Identifying valuable data sources — often due to lack of a data catalogue

The Verdict

A combination of human expertise and machine learning should be used for monitoring and learning about each step and optimizing the pipeline, delivering the ability to explain results and adjust the pipeline more rapidly as the external environment changes.

Organizations need to follow these 6-step process to optimize their data pipeline and derive maximum benefits on their analytics ROI

1. Invest in technology solutions to address each step of the data-to-insights pipeline

2. Hire a team of data, analytics, IT, and business subject-matter experts

3. Ensure that the data architects, data engineers, business analysts, data scientists, designers, and developers collaborate to create agile pipelines that underpin the new generation of enterprise intelligence

4. Optimize each stage of the data pipeline to boost its overall benefits

5. Design a pipeline that embraces rapidly changing data architectures and cloud technologies while providing the necessary agility to use these new innovations for competitive differentiation

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