In today’s COVID-19 crisis, it is essential for enterprises to utilize and optimize every technological aspect of their infrastructure. The insights provided by big data have been a turning point for many enterprises to survive and thrive in the current economic crisis. Enterprises that fail to strategize their data effectively are witnessing downward trends in their growth and revenue chart.

Therefore, it is essential for enterprises, to have strategies in place that will help them to avoid the big data mistakes, before embarking on their journey to leverage data.

• Rethinking about The Metrics

Today’s dynamic place, coupled with the economic strain inflicted by the COVID-19 pandemic, is forcing enterprises to keep evaluating and adapting advanced strategies and solutions. But most enterprises are still finding it difficult to let go of their conventional key performance indicators. Hence, enterprises must use novel and appropriate tools to extract the analytics that provides insights into the driving forces of business.

• Reevaluating Data Security

Implementing and integrating big data and analytics projects to drive the business forward is an excellent move. However, not having sufficient security and compliance protocols in place, can make these projects a hotbed for cyber attackers to exploit the database and steal confidential enterprise information.

Therefore, enterprises should take a comprehensive approach to protect the big data. This must include a thorough understanding of the available data, auditing its manipulation, and a stronghold over the users with access to the data. At the start of a new project, enterprises should have their discussions in the terms compliance, governance and enterprise cybersecurity.

• Technical Costs?

Before starting the big data project, there are a significant number of changes that enterprises must focus on. However, at present, many enterprises underestimate the criticality of these changes. They focus on the technical costs to deploy the strategy while leaving behind other factors, outside of the technical investment that can develop potential challenges.

Therefore, enterprises should thoroughly evaluate the technical investments of projects such as planning budgets for skill development, training and change management within the enterprise. This can lay a strong foundation for a culture to effectively utilize big data analytics.

• Utilizing External Data

Today, data has become hugely diverse. It comes in myriad forms, not just as databases and spreadsheets, but also as Photos, sound recordings, text files, and many other forms of raw data that businesses collect. This data is often unstructured, and hence, most find it difficult to appropriately utilize it.

Though having a data strategy which is robust and accounts for structured and unstructured data can provide meaningful insights, overlooking external data sources such as data repositories, governments and data brokers can hamper the progress of data. Extracting value from each dataset at the disposal can help enterprises to progress and add value to the business.

The above metrics are some of the many ways that enterprises can avoid in their big data project. This will not only help them to progress further but also allow them to set the right standards for future big data projects, resulting in reduced cost and skyrocketing the growth and revenue.

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Today, Hewlett Packard Enterprise (HPE) announced its acquisition of MapR business assets. MapR began as a company focused on providing a cloud data platform. They extended their message into machine learning (ML) and artificial intelligence (AI), claiming to be good support for data sources needed in those arenas. In addition to the cloud, they focused on a container message for scalability. They had some early backing, but that backing wall pulled earlier this year.

Phil Davis, president, Hybrid IT, Hewlett Packard Enterprise, said in the press release, “MapR’s enterprise-grade file system and cloud-native storage services complement HPE’s BlueData container platform strategy and will allow us to provide a unique value proposition for customers. We are pleased to welcome MapR’s world-class team to the HPE family.”

The press release also focused on the partners in the AI/ML and analytics markets more than it did on the technologies.

What’s interesting to note is that no price was announced for the acquisition. In addition, the stated purpose of working with BlueData, another acquisition focusing on container-based software for AI/ML should make folks wonder about the purpose and benefit of the acquisition. What we have is a second acquisition in the same space, but the MapR one is of a company from with the backers withdrew funding. It is reasonable to assume that HPE acquired it for the connections into the market and not for the technology. Could they have just paid for the lead list and for the partner relations?

From a non-financial evaluation, the larger companies are continuing the fast follower strategy mentioned in my previous article, but MapR didn’t have the presence that OpenAI had, pre-acquisition. I’m sure HPE didn’t pay as much as Microsoft did, but there is still a lot left unanswered in the press release and related material. That means there is no way to evaluate what kind of sense the acquisition makes.

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