Cloud-enabled business transformation has become a priority. This is as organizations grapple with global supply chain issues, cybersecurity threats, and geopolitical instability. All organizations of all sizes and vertical markets turn to the cloud. With this, they guarantee flexibility and resilience in facing these challenges. However, small and midsize businesses have driven investment in cloud infrastructure services to support workload migration. Also, data storage services and cloud-native applications. Developing.

Cloud-based data warehouses, data lakes, and lake houses played a prominent role in 2021, with respondents (48%) citing them as a top initiative and top use case (57%). The hybrid cloud remains the preferred deployment model, as it has been since the 2020 survey. However, this year, the gap between hybrid and private clouds is much more significant. The hybrid cloud was chosen by nearly twice as many respondents (37.5%) compared to the pure public cloud at 20%. This year, it’s clear that the hybrid cloud is less of an “option” than a “necessity” and indicates that businesses aren’t ditching their on-premises systems even though they have increased their presence in the cloud.

Most companies have reached an “intermediate or advanced level” of cloud usage
Companies have good reasons for implementing this mixed deployment style, including regulatory compliance.

For these data-driven companies surveyed, nearly four in five respondents ( 79%) cited the complexity of data integration. Also, the accessibility of data and the adaptation of different data formats as the main barrier to becoming data-driven companies, followed by the lack of analytical capacity.

Data scientists also struggled in this survey. They were often cited for spending more time searching, accessing, and preparing data than analyzing it. More than 2 in five (44%) could not find, access, and analyze half or more of their data after adopting cloud technologies, and only 17% could leverage 75% or more of it.

T’s role in the cloud modernization process has also changed. In 2020, tech professionals focused on choosing the right cloud provider and managing the migration. But in 2021, these IT teams are more focused on getting the training they need to take their organization’s cloud systems to the next level. Other activities, such as cloud provider selection and migration planning, remain essential.

Companies use the cloud for various use cases, with reports and dashboards being the most popular ad-hoc analysis and self-service BI. However, respondents anticipate a shift toward data virtualization, data preparation, data quality, and blending.

These use cases vividly depict where many organizations are with their journeys to the cloud. First, it reflects that business stakeholders within organizations are ready to use their data better. Second, it shows that organizations are now looking to maximize their cloud systems with robust cloud-based repositories. The next step for many companies is to find a place to store the new data that they then begin to acquire.

Also Read: Big Data, Cybersecurity and Cloud Systems, The Disciplines Where There Is Employment

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Data quality considers criteria like correctness, consistency, integrity, and usability when determining the state of your data. A perfect score in each of these areas indicates high-quality data, which is the optimum type to employ for processing and analysis.

One of your company’s most valuable resources is data. Poor data quality practices can cost businesses a loss in their revenue. The quality of the data you feed your business intelligence is only as good as the data you supply it. Make sure your data analysis isn’t losing value because the data it’s fed isn’t correct.

Today data-driven organizations increasingly rely on insights, customer databases, and marketing efforts and drive vital business decisions from these data thus high-quality data has become increasingly important. Inconsistent or incomplete data can erode client trust and harm your standing in the market.

How to measure the quality of the data?

It is required to assess the quality of data regularly to make sure that the data is working to its full potential. According to a Gartner study, there are six points of reference for data quality management:

1. Consistency: When data is stored in multiple locations, check whether the values are the same.
2. Accuracy: data should accurately describe the properties of the object it is meant to model
3. Relevance: data should be appropriate to support the objective
4. Existence: the organization have the right data to use
5. Integrity: relationships between data elements and data sets should be accurate
6. Validity: the values should be acceptable

The majority of businesses rely on software to detect and repair errors. Data quality technologies, which ensure that an organization’s data is clean and valuable, are plentiful. Many programmes include capabilities like programme management, responsibilities, use cases, and procedures (such as monitoring, remediating, and reporting data quality) as well as organizational structure creation. Informatica Data Quality, Microsoft Data Quality Services, and Oracle Enterprise Data Quality are some of the most popular current market products.

Your data can be repaired if it isn’t in good shape. The four steps below can be used to develop a strategy for overcoming data quality issues.

1. Establish data oversight departments and executives, and provide them with the tools they need to establish effective quality standards.
2. It is important to measure the value of your data. Measure the quality of your information assets, as well as the cost of poor-quality data. These figures can be directly linked to critical business measures.
3. Estimate the length of time it will take to deploy data quality software. Many businesses wrongly estimate this amount of time which results in mistrust between business operations and information technology.
4. Make the most of your data quality software. Because this type of software isn’t cheap, keep your costs down by remaining adaptable and focusing on value while maintaining your high standards.

Data quality management strategy

To avoid a data crisis, you’ll need a solid data management strategy. Data management is possible with the help of a team that will be stewarding operations. A CDO to assure top-level management engagement, a programme manager to oversee daily activities, and a business analyst to establish organizational needs and ensure that they are communicated to developers.

Another important aspect of data management is Data Profiling. Reviewing the data, comparing it to metadata, running statistical models, and final reporting are all steps in the process. Data profiling provides a starting point for the process and aids in the establishment of standards within the company. In the management process, data repair can come after profiling. It includes determining why and how data errors occurred, as well as the most efficient strategy for repairing them.

Conclusion

To conclude we can say that data quality is an essential part of an organization. It’s critical for increased operational efficiency, cost savings, and a data-driven decision-making foundation. A successful analytics operation is easier to manage and more accurate with high-quality data, even when faced with quickly expanding volumes, and will give dynamic insights to everyone.

Also Read: Big Data – The Strategic Ally Of Electronic Commerce

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Do you know where your data is?

If you’re like most business leaders, the answer to that question is an emphatic ‘no’ – and that’s a problem. By now, you’ve doubtless heard about impending regulations like the European Union’s General Data Protection Regulation. For those few of you who are still unfamiliar, the gist of it is as follows.

It greatly expands the level of ownership and control citizens of the European Union have over their personal data. Businesses must be completely transparent about how they use the information they collect, and they need to have consented to both collect and process it. And that consent can be withdrawn at any time, at which point all data must be scrubbed from the organization’s servers.

That’s unsurprisingly a little tough to do if your data hygiene is akin to a digital pig’s pen. Of course, I don’t doubt that some of you probably don’t see this as much of a big deal. After all, this legislation just impacts the EU and anyone who does business with EU citizens.

If you don’t have any plans to do business with anyone from that region, it’s of no concern to you, right?

Wrong. While the above does currently hold true, other global governments have taken notice of what the GDPR entails. Already, we’ve seen countries like the United Kingdom and Australia implement their own legislation. Others, like Canada, are on the verge of doing so.

Easier compliance with privacy legislation is far from the only reason why better data organization and visibility is worthwhile. It also makes it far easier to protect yourself against data breaches. If you know where everything is located and how it’s generally used, you’ll be able to determine straight away when something is being used improperly. 

Beyond that, there’s the matter of making better business decisions. You’ll know how your application and file infrastructure look – meaning you’ll know what areas need the most funding and attention. Moreover, you’ll be able to better detect negative trends and bottlenecks which might impact your business’s productivity.

Finally, by taking user privacy seriously and giving your people ownership of their personal data, you’ll foster no small amount of goodwill with your customers. They’ll see your transparency and openness as a sign that they can trust you. And as a result, they’ll be more willing to do business with you again in the future.

Better compliance and security. Improved visibility, decision-making, and spending.  A better relationship with your customers.

There’s really no reason not to take charge of your data hygiene and figure out where everything is located. Really, the only question left is why you haven’t already done so. Hire yourself a GDPR compliance officer, track down an enterprise file sharing and synchronization platform, and start organizing your file system.

Trust me, it’ll be worth it in the long run. 

Also Read: How To Have A Good Presence On Social Networks?

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