Analysis Using Big Data

Major Do’s and Don’ts of Data Analysis Using Big Data

There are many businesses and enterprises which are newly into exploring the scope of big data and taken initiatives to implement its early-stage execution. For those who are new to big data analysis, here are some do’s and don’ts to consider as a part of the big data strategy. Most of these companies are now experimenting with the pilot processes to see if they can leverage the big data sources in order to transform their business decision making and strategizing. At this phase, it is easy for someone to make mistakes which may ultimately cause disruption of the business strategy.

Involving big data in your strategy

As many take it wrongly, big data cannot be a standalone activity. But it is a unique way through which the businesses can leverage volume data highly in order to learn more about the processes, customers, and events which could come as snapshots of insightful data. Once if handled properly, a good big data strategy will have a great impact on your business strategy and increase its effectiveness multifold.

Organizations which assume that their data is way out of the norms may discover many emerging reassuring patterns of consumer requirements. All types of business units can gain a significant value if they are brought as early as possible into the process.

Evaluate all big data delivery models

For those who are new into it, it is quite natural to think that it is ideal for managing the data in a data center if the volume to handle is huge, i.e., in petabytes. However, technology is now evolving in a far much faster pace to make it possible to use the capacities of cloud computing storage to manage big data resources. You may evaluate the capacity of such cloud-based services and consider which providers could probably meet your performance needs.

Traditional data sources in big data

There are many organizations which now find value in big data analytics but assume that they need not have to think of traditional data warehousing. This also is not an ideal approach to big data. It is so critical that one should plan to effectively use the big data analytics insights in relation to the conventional data warehouse for best results. The data warehouse will have information about how your company operates and all historical data too. So, comparing the big data results against your core data benchmarks is crucial for effective decision making.

Plan for a consistent metadata

While you finish with the analysis of massive data sets with the help of providers like, it becomes easier for you to come up with more tangible data that match the patterns. This set of data can be further used for organizations to analyze the issues in depth. Keep it also in mind that that this data may come from various sources as social media or customer service platforms. It is also an important fact to not this these raw data are not cleansed. So, before you trust the relevance of data, ensure that you are dealing with consistent metadata set in order to bring this information into the organization and then analyze it solidly by making use of the data form your records.

Effective distribution of big data

While dealing with big data, never assume that you can fully manage all such info in a single server. Check and find out how to utilize distributed computing platforms like Hadoop to manage the data size effectively and set the required speed to manage the data. Another fact to note is that there is a recent hype in the market around technologies like MapReduce and Hadoop that the users may lose clear sight as to what needs to be accomplished.

There are plenty of technologies available like text analytics, data streaming environments, predictive analytics, spatial data analytics, etc. which also may be crucial in your job while trying to do data analytics. So, take your time out and investigate in-depth about a variety of technologies which may support you in the job. You should experiment with various technology solutions to see, which could be used successfully for your purpose.

Don’t try to upsize your data before you are all set

It is easy to become excited about the potential of big data for your organization. It is known that big data could make a huge difference between simply jumping into a new market before the competitors thinking of it or just be left behind in the competition. So, first, walk steadily and then speed up to run. You may start with the pilot projects which may allow you to gain some solid experience and try to work closely with the experts until the stage that you don’t tend to make any mistake due to inexperience.

Never overlook the need for big data integration

Big data sources may not be effective in isolation, and these cannot be on any value if taken independently. Major big data technologies available in the market lately are focused on making things easier for the users by integrating the analytical resources to other sources of data. So, always be prepared to integrate the data on one hand while analyzing it on the other.

Always manage big data securely

While the businesses start to use big data analytics on a larger scan, most of them forget to maintain a considerable level of data governance and security as assumed in the traditional data management environment. When you start the analysis of the huge volume of data in petabytes, one shouldn’t ask any private information at the outset. However, if you have the subset of the initial data which his crucial in terms of identifying your next course of action or your market approach, then you have to secure the data to avoid putting your business and risk of the data leak. Such data is considered as the intellectual property or corporate which needed to be fully secured.

Overall, big data demonstrate the need for all to be become more data-oriented than before and handle it a faster speed than ever. This enables the business to get a more insightful approach to high volume business administration. On the other hand, if the big data available is not managed properly, then it may end up in big problems too for the company. So, first built manageability into your business road map and then plan for big data implementation.

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