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Ready to Start Using Big Data?   Featured

Ready to Start Using Big Data?    Campaign Creators

Over the past two decades, data has emerged as one of the most crucial points that professionals in different sectors have continued to discuss. With the importance of data in decision-making, businesses in sectors such as healthcare, financial services, and agriculture are turning to big data as they seek to enhance efficiency and add untapped value to their operations.

A study by Forrester Consulting indicated that 40% of businesses use big data analytics in key business functions of the organization. However, despite these organizations' progress, most do not know where they should start in terms of using the wealth of information they have in their possession. Further, the survey pointed out that 63% of organizations are mature in the data space.

As you think of venturing into the big data and analytics space within your organization, here are a few points that might help you get started.

  1. Identify use cases

When starting a big data project, the first step should never be jumping into the project directly. Rather, it is crucial to identify and define the reasons for doing so. These include aspects like understanding the nature of your business, personalizing promotions and minimizing the cost of operations. Start by informing people from different about Big Data and analytics so that everyone within the organization can understand the importance of this technology. Run workshops to enable everyone to learn and exchange ideas.

  1. Identify and qualify data

Determining the relevant data for the selected user is the second and critical state in a big data project. Highlight the source of data and their origin, which can be internal, social, partner-based or public. Also, identify the type of data, format, quality and availability.

  1. Prepare the project

As you think of starting a big data project, think of a way that will allow you to move quickly ad avoid roadblocks during the implementation stage. This can be addressed by the agile approach, which brings together all the necessary skills. The multidisciplinary team includes data scientists, architects, data analysts, technicians, and a project manager.

  1. Set up the data platform

While all big data platforms are important, not all are made the same. Rather, the components in a big data architecture will depend on the needs of the customer and the available data and use cases. Therefore, the tools that need to be used must be assessed on a case-by-case basis based on their needs.

  1. Data collection

For appropriate collection channels to be set up, you need to ensure that you understand the volume of data and the depth of historical data. You need also to understand the nature and complexity of data flowing to the organization. After that, look at the preparation of data and the quality of the data gathered. Ask yourself if the data needs to be sorted, cleaned and enhanced. Identify the right processes and tools that should be used in the process. Determine the infrastructure and the storage type that the data needs.

  1. Analyze processing

 Depending on the uses cases, select the right method of analyzing data. Ask yourself if the analysis should be done in real-time or in batches. While at it, ask yourself whether you are looking for correlations, trends and anomalies or whether you are seeking to discover, explain or predict possible trends.

  1. Visualization of data

Offer users information that they can understand easily and access using the right data visualization tools. With big data projects becoming increasingly widespread in the corporate world, their benefits are emerging. As projects become increasingly deployed, the right big data governance approaches must be laid down to ensure security, confidentiality, traceability, backup and access are respected.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

scottkoegler.me/

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