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Seven Data Management Trends You Can Leverage In 2021

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Source: Forbes.com/ Daniel Hussem

Comment: We highlighted “Big Data” in a recent article but this article delves much deeper into the upcoming developments and some food for thought on what you may need to be planning ahead for. Some of the point are more relevant to large companies but Data Visualization is highly relevant for all SME’s. It’s important to look ahead and be aware of Data trends coming down the track.

The phrase “big data” has been around for well over 15 years, since the development of Web 2.0, and organizations have been collecting (user) data for decades. Yet only about 1 in every 4 companies can claim to have a well-defined data management policy and structure.

If you are looking for new trends in the data-driven space and could use some data management guidance, here are a few trends you could leverage to improve your service offerings moving forward.

1. Augmented Analytics
In the past, data analysts spent the majority of their time collecting, preparing and organizing data for analysis. Augmented analytics will automate most of the data analysis process, which will leave humans more time to find use-case scenarios for insights received.
Augmented analytics uses machine learning and natural language processing to help process and improve analysis processes normally done by a specialist or data scientist. It can develop, manage and help users deploy artificial intelligence models. Your organization can now collect and review thousands of customer reviews in a day.
As the field grows, organizations will also leverage continuous intelligence. Real-time analytics will see businesses reduce the time between getting new insights and integrating them in their decision-making. This will increase efficiency and competitiveness in the market.

2. Self-Service Data Management And Analytics Tools
Data democratization is an ever-bigger need for front-line marketing and sales professionals. I dug into this elaborately in one of my prior publications and cannot stress enough the importance of self-service tools to efficiently analyze and manage data assets without requiring specific technical expertise or training.
Your marketing and sales teams need to be hands-on with their data and not be dependent on IT to operate their assets. Give them the tools they need to handle their day-to-day data requirements and operations.

3. Cloud-Native Solutions For Data Analytics
2021 and beyond will see the conversation around analytics shift from the cost of services to best-in-class solutions. The cloud analytics service sector is growing rapidly.
Using cloud analytics over on-premises analytics offers numerous advantages. It frees up your in-house data team to take on other tasks that directly contribute to your bottom line instead of maintaining the hardware. It allows you to easily spin up or shut down machines based on workload, helping you to scale seamlessly and cut down overhead costs. And with cloud computing being as powerful as it is today, it will surely meet your organization’s performance requirements.
Cloud analytics services provide data models and advanced analytics tools that businesses would otherwise have to build themselves. Now organizations only have to pay for what they use.
According to Gartner’s prediction, 90% of solutions in the data analytics field will use this model by 2022.

4. Hiring A Chief Data Officer
Find out whether your organization has reached a threshold where the amount of data you collect warrants having a chief data officer (CDO).
One decade ago, data scientists were virtually non-existent in many organizations. Their role slowly grew from software engineers taking on extra responsibilities as the field of data grew.
Today, organizations need top-ranking officers (C-level) to take up the essential role of securing and leveraging big data trends. They are responsible for governance matters, identifying areas where data can improve the client experience and data analytics can improve productivity and sales.
In most organizations, the CDO reports directly to the chief executive officer (CEO). The CDO then has a team of data analysts, engineers and developers, depending on organizational needs. Theirs is largely a strategic role.

5. Taking Advantage Of Data Exchanges
There are numerous advantages to monetizing any data you collect and have the rights to resell. First and obviously, it’s a way to grow revenue. But perhaps more importantly, it is a way of forging symbiotic relationships with other companies. Organizations can exchange data directly or through secondary markets. In either case, the establishment of relationships can lead to competitive advantages through insights previously unavailable.
In addition, data quality is essential for monetization. Internal processes must guarantee the accuracy, security and organization of such data.
Establish an actionable policy on data governance at your firm. There are challenges in developing data as a service business models owing to ethical and privacy issues, but numerous companies have already taken on the challenge. As highlighted, hiring a chief data officer could help build a viable solution.

6. The Use of Blockchain And Distributed Ledger Technology
There is a new trend in the market where some companies are slowly replacing traditional databases with a distributed ledger system. Distributed ledgers promise a more secure record of transactions, smart contracts, asset tracking and audit trails.
The biggest challenge to the adoption of distributed ledger technology is a general lack of understanding of how it works and embracing blockchain technology as a whole.
Blockchain and distributed ledger technology store data in a decentralized form. The data stored in such a way is immutable. When you store a transaction in blockchain, for instance, it cannot be altered. Such will be the case for the other transactions that follow it. It creates an easy-to-audit, “foolproof” trail.

7. From Data Visualization To Data Stories
A simple dashboard is no longer useful. Interactive data stories are far more compelling than static dashboards.
Your organization needs to present your data findings in a manner that tells why the information matters. Data stories contextualize everything.
Data visualization is a separate vertical within data management. Visualization specialists are charged with creating a narrative around each chart and making aesthetically pleasing, dynamic presentations.

The Takeaway
Data management is far from static, and in the new decade, every data-driven organization must find ways to collect, analyze and make business sense of their ever-growing data assets.
It may sound daunting or complicated, but it does not need to be. As highlighted, the evolution toward public cloud-native services makes data analysis accessible, affordable and nontechnical. You can get data insights without learning or knowing how to code using self-service data management tools. It is the democratization of analytics and data management for all.

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