Microsoft continues to tear down silos with the public release of Azure Synapse – announces Azure Purview, a new data governance solution.
If you work with data (well, who doesn’t?), you understand how crucial information can be for organizations, especially easily accessible or available information. In most organizations and businesses, data is the driving force, influencing everything from customer connections and experiences to marketing strategies and new product development. In other words, data is king.
According to Forbes, 49% of those polled believe data analytics helps them make better decisions, 16% believe it facilitates achieving major strategic objectives, and 10% believe it improves connections with consumers and business partners. The basic line is that data is necessary for structure, progress, and opportunity.
However, what happens when that data isn’t easily accessible or shared across departments, and how can businesses and organizations overcome this barrier to better position themselves for opportunity and growth? Imagine spending a significant amount of time attempting to acquire a piece of data. Think about your company struggling with time-consuming customer service interactions because the necessary information isn’t easily accessible.
In this blog, we will discuss data silos and how to eliminate them with Microsoft Azure –
What Is a Data Silo?
When data is kept in many places or is separated from other sections of the company, it is referred to as a data silo. The marketing and sales teams, for example, employ various data warehouses. Because separate departments have access to different systems or data sources, alignment issues might arise. In certain circumstances, divergent information might lead to various teams within an organization analyzing data and reaching different conclusions since they aren’t seeing the whole picture.
What Causes Data Silos?
There are four primary reasons for data silos to exist:
Organizational Working Culture
– Departments and teams in most firms tend to function in isolation. This is especially noticeable in larger corporations. Because teams see themselves as independent from the organization, this isolation can rise to internal competitiveness. Silos emerge as a result of a lack of information exchange.
– As a firm grows, it frequently incorporates new technology, SaaS services, or a separate data warehouse. Different functional units may have their database or draw data from several sources. It has become normal to have various information systems inside the same firm that are not meaningfully linked together.
– It is typical practice in a company for various departments to utilize a variety of apps. The sales team, for example, may utilize Salesforce, while the marketing department employs HootSuite, and the media team employs SproutSocial. Each of these applications has a wealth of information that, if shared, might benefit every team. According to surveys, corporations may utilize up to 1200 applications across departments. As a result, there are various sources of knowledge that might be difficult to communicate.
– Funding (or a lack thereof) might lead to data silos in several circumstances. Businesses and organizations may believe that change is expensive or that the return on investment from transferring information out of its silo is insufficient.
Siloed data can have a negative influence on an organization as a whole. A data silo restricts the team’s visibility of the data. When there are several organizational silos, it can cause substantial challenges in how people and teams work together to achieve a single purpose.
How to Eliminate Data Silos
The appropriate data silo solution will integrate your data and systems, increasing organizational efficiency and consistency. You will save time and money by adequately integrating all of your separate data sources, as well as ensuring that you are transforming data culture and management for the better.
Microsoft Azure Synapse is an analytics solution that rapidly and effectively offers insights from all of your data. It accomplishes this by combining enterprise data warehousing and big data analytics, allowing you to query data on your terms. This all-in-one solution improves query efficiency while also offering a unified analytics experience that combines Power BI and machine learning.
Here are the measures that you must do as a group to break down silos –
Take Care of Cultural Issues
When it comes to removing data silos, cultural challenges may be the most difficult to overcome. These impediments may be long-standing, particularly in distinct departments. While team members may appreciate the necessity at a high level, the rest of the company may be perplexed as to how to handle the critical aspects required for complete data integration to occur.
Establish a Centralized Data Repository
Creating a centralized data repository is the most effective strategy to remove data silos. It’s time to set up a data warehouse or data lake to contain all of the data your company collects. Whether on-premises or in the cloud, data from diverse sources must be integrated and made available across a company so that employees have easy access to the essential information they require.
When data is entrenched across a company, business intelligence functions best. It is critical to have the correct information at the right time for analysis and to make better business decisions. Such data, however, will not be available if data is incorporated into your organizational structure. Data integration may be achieved in a variety of ways – On-premises ETL, Scripting, Cloud-based ETL.
Improve Your Data Governance
Data governance is critical for firms that use bid data to assure the data’s integrity and security. It ensures that information collection, storage, access, security, and compliance are all applied consistently as data travels through an organization. To prevent establishing a new business silo, whether the sales team, marketing team, or any other department inside the company is dealing with data, they will all come under the data governance framework.
Advanced analytics are enabled by Azure Data Services, allowing you to optimize the business value of data saved in CDM files in the data lake. Data engineers and scientists may utilize Azure Databricks and Azure Data Factory dataflows to cleanse and reshape data to ensure its accuracy and completeness. To optimize data for analytics processing, data from various sources and formats can be standardized, reformatted, and integrated. Data scientists may use Azure Machine Learning to create and train machine learning models on data, resulting in predictions and recommendations that can be embedded in BI dashboards and reports and utilized in production applications.
Data engineers may use Azure Data Factory to mix data from CDM folders with data from throughout the organization in Azure SQL Data Warehouse to generate a historically correct, curated enterprise-wide picture of data. Data processed by any Azure Data Service may be written back to new CDM folders at any time, making the insights developed in Azure available to Power BI and other CDM-enabled apps or tools.
Learn and upskill with Microsoft Azure
Cognixia’s Microsoft Azure training is intended to assist professionals in preparing for the AZ-104: Microsoft Azure Administrator certification exam. Professionals who complete the AZ-104 course will have an advantage in a highly competitive IT employment market.
Enroll in Cognixia’s AZ-104: Microsoft Azure course to improve your abilities. With our hands-on, live, interactive, instructor-led course, you can shape your career and future. In this competitive world, we are here to give you an exceptionally intuitive online learning experience, to help you in expanding your knowledge through interesting training sessions, and add value to your skillset. With our online interactive instructor-led courses, Cognixia caters to both individuals and corporate workforces.
This Azure training helps IT professionals learn how to manage their Azure subscriptions, administer the infrastructure, secure identities, configure virtual networking, manage network traffic, connect Azure & on-premises sites, implement storage solutions, implement web apps & containers, create and scale virtual machines, back up & share data, and monitor the solution.
The following topics will be covered in this AZ104 training:
- Module 1: Identity
- Module 2: Governance and Compliance
- Module 3: Azure Administration
- Module 4: Virtual Networking
- Module 5: Intersite Connectivity
- Module 6: Network Traffic Management
- Module 7: Azure Storage
- Module 8: Azure Virtual Machines
- Module 9: Serverless Computing
- Module 10: Data Protection
- Module 11: Monitoring