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How to Overcome Cybersecurity Challenges
With AI
May 02, 2018

Multi-Location Data Management Is a Competitive Advantage

Data management is a complex challenge. After all, data isn’t just getting bigger—it’s also expanding exponentially across a wider range of locations. Enterprises must deal with the challenge of information being spread across multiple locations, whether in data stores, systems, or various types of cloud (private, public, and hybrid).

This data sprawl creates a big issue for IT decision-makers and the businesses they support. Modern businesses aim to create a 360-degree view of their customers, in which information is aggregated from various sources and a single instance of the truth is possible. The reality, however, is that creating this consolidated customer view across multiple data sources and locations is a challenge.

Multi-location data management is the key. To really make sense of the knowledge it holds, your business must create a common data-management layer, so your business and personel can deal with the organizational challenges associated with securing, governing, and managing this information.

Understanding Data Management

Multi-location data management is emerging as a key competitive advantage for organizations, according to 451 Research. The analyst group recognizes that identifying available data and where it resides across multiple data centers and cloud providers is a growing challenge for IT decision-makers.

Data is held in applications from a disparate range of vendors. Information also comes in a variety of guises, ranging from the structured data held on corporate databases to the unstructured sentiments about brands found on social media channels. An organization that is unable to bring all its data together will not be able to make fully informed decisions.

For example, retailers that rely only on sales information will miss out on the potential impact of social sentiment and pricing preferences. They won’t be able to understand how sending a just-in-time coupon affects a customer at the point of purchase. Such data management can make the difference between a lost client and a new sale.

Building a Layered Approach

Organizations that want to make game-changing decisions quickly will need to act on their integrated data sources in real time. To enable multi-location data management, decision-makers must help their businesses implement the right technologies.

A data lake can provide the platform to bring your data-at-rest together, allowing your business to bring all its various sources of information into a single store. At the same time, however, you’ll also have to deal with the data that’s in motion—so you should look to integrate real-time sources, such as IoT, social feeds, clickstreams, etc., too.

The final management layer should run across your data lake and data flow technologies. This layer should give your business a single view of truth. It will provide ways to delve into insights and to deal with some of the key characteristics that help ensure successful multi-location data management.

Key Characteristics for Success

Data agnosticism is crucial. Whether the source is a data lake, an application, or a screen, your business should be able to treat information as a single entity. If the data sources are treated agnostically, it will be much easier to deal with the other key management features:

  • Security: Much of the information your business holds is sensitive: think of the human resources information scattered across multiple data sources, such as human capital management systems, payroll stores, and performance-metric tracking applications. Your business will need to provide a common security platform so that the right people (and only the right people) will be able to access the information at the right time.
  • Governance: The digital era is characterized by its focus on data compliance. The forthcoming General Data Protection Regulation (GDPR), for example, places potentially onerous constraints on organizations and individuals who process information. Your business must give auditors visibility into data access points and changes. Good governance relies on a clear view of the life cycles of the information your firm holds.
  • Backup: Data moves through different stages during its life cycle: first, it’s active and in use, then it’s stored in backup—until it’s required again. It’s extremely important that the data backup process, including disaster recovery, runs on a regular basis. Rigorous management of the entire data management life cycle is a crucial factor for success, despite the fact the increasing sprawl makes it more and more challenging.

Leading From the Front

Organizations looking to deal with the combined concerns of security, governance, and backup must give data management executive priority. While CIOs have traditionally taken responsibility for information governance, Wired reports that many organizations are now appointing dedicated chief digital or data officers (CDOs).

CDOs should establish a strong data management strategy, working alongside a governance committee to ensure that processes and frameworks are created and followed. The CDO should cover a range of key concerns, from establishing service-level agreements for disaster recovery to helping create a single view of data.

The success of your data management strategy will come down to the development of a tightly integrated team. This should be a cohesive group—including scientists, engineers, and architects—that works with the data executive and the governance committee to ensure that data management is always a business priority.

Great Data Management As a Competitive Differentiator

Digital transformation is a critical business objective. To drive effective business change, your business must establish a 360-degree view of its customers. The visibility of data at the right time creates success. A multi-location data management strategy will help your organization consolidate information and generate the insight you need to succeed.

Read more about missteps to avoid as your company embarks on a big data journey.

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