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Top 10 Big Data Pain Points

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Big data is the flavor of the season, with companies cutting across sectors and size lining up to get on the big data bandwagon. However, it is at implementation time, and even later, that many companies come face to face with the harsh realities of big data. All the potential and advantages it offers comes only if the pain points that come along with it are resolved. Here are the top 10 pain points associated with big data.

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Published in: Technology
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Top 10 Big Data Pain Points

  1. 1.  Big data is the flavor of the season, with companies cutting across sectors and size lining up to get on the big data bandwagon.  However, all the potential and advantages of Big Data come only if the pain points that come along with it are resolved. Big Data- A matter of concern
  2. 2. 1. Data Trapped in Silos  The first challenge that comes to any big data analyst worth her byte is consolidating across the enterprise.  Data is not just spread across multiple repositories, but is invariably trapped in silos, many of which are inaccessible or not online.
  3. 3. 2. Data Overload  Data is growing at an exponential pace in today’s highly digital world, and before an organization knows it, they are submerged with massive datasets.  Simply collecting every bit of information simply loads up the data warehouse and analytical engine with large volumes of mostly useless data.
  4. 4. 3. Data Interpretation  It is important to understand where each piece of data came from, and how it may be best used.  Data visualization, or presentation of information in a graphical or pictorial format makes it easier to understand information.
  5. 5. 4. Data Cleansing  Raw data, or the data that comes in may not have appropriate headers, might have incorrect data types, or might contain unknown or unwanted character encoding.  It is essential to modify the raw data to get rid of these discrepancies, for consistency.
  6. 6. 5. Technical Challenges Related to the Processor  GPUs or graphics processor units do the job well than traditional CPUs that may simply not be able to withstanding the load.  GPUs cost a lot less than CPUs in any case, but the pain point is the difficulty in programming GPUs
  7. 7. 6. Handling Huge Data Volume in Less Time  Companies today require a resilient IT infrastructure capable of reading the data faster and delivering real-time insights.  Many standard commercial packages such as Apache Hadoop IBM InfoSphereBigInsights, Cloudera, and Hortonworks are capable of resolving such challenges
  8. 8. 7. Scalability  It is important to get the interaction between storage and processing correctly.  Scaling multiple workloads however pose a challenge and at times, it may be required to expand and distribute storage on a temporary basis.
  9. 9. 8. Security  Big data inputs come in from multiple sources, and it is important to ensure that all the data that comes in are secured.  Big data processing takes place in the cloud, and all the inherent security risks of data theft are ever-present.
  10. 10. 9. High Budget Big data analytics is costly, and costs can very easily overshoot estimates. With the amount of resources and man power required to set things up it always becomes a heavy budget project.
  11. 11. 10. Selecting the Appropriate Tool for Data Analysis Deciding on the approach taken to collect, store, and analyze data is one thing, and deploying suitable tools for analysis quite another. Organizations need to spend considerable time before selecting an appropriate tool for analysis, for it is difficult to move an application from one tool to another.
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  13. 13. That’s not all, feel free to share this information
  14. 14. For any queries on BIG DATA
  15. 15. Suyati provides marketing technology and integration services for companies that wish to combine the best of breed solutions and create a unified approach to customer acquisition. This unified digital marketing approach requires system integration between various CMS and CRM platforms, and a slew of eCommerce, Marketing Automation, Social Media Listening, email and social marketing, and customer service systems. Our specialized knowledge in Salesforce, open source and .Net based systems enables us to build effective custom integrated solutions for our clients.

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