The Evolution of Data as an Asset

Enterprise data is the most valuable asset for businesses today, but it also presents significant challenges. Businesses are collecting and utilizing more data than ever before. With this influx of data, organizations are tasked with finding ways to store, manage, and analyze data efficiently and effectively. The challenges associated with enterprise data will only become more complicated as businesses become more data-driven in 2023 and beyond.

Here are the three biggest challenges businesses face today:

Data Management - To effectively use data, businesses must be able to store and access it quickly and accurately. Without the proper systems and architecture in place, data can become unmanageable and inaccessible. Additionally, businesses must be able to detect and respond to any potential security threats. To do this, businesses must have robust security systems in place to protect their data from malicious actors.

Data Integration - As businesses continue to acquire more data, it is becoming increasingly difficult to integrate new data sources into existing systems. As a result, businesses are often unable to effectively utilize the data they have collected. To effectively manage data, businesses must be able to integrate new data sources quickly and efficiently.

Data Analysis - This requires businesses to have access to the right data analysis tools and the right personnel to interpret the data. Without the right tools and personnel, businesses may be unable to gain actionable insights from their data.

As we look ahead to 2023, businesses will need to develop effective data strategies to address these challenges:

Implement robust security measures to protect data from malicious actors and invest in data integration solutions to effectively utilize data from multiple sources
Focus on developing data analysis capabilities to gain insights from generated data
Invest in Artificial Intelligence (AI) and Machine Learning (ML) solutions as these can be used to automate data processing and analysis tasks, allowing businesses to gain insights more quickly and accurately
Develop ethical data practices to ensure that enterprise data is used responsibly

With technology constantly evolving, businesses must develop new strategies to address enterprise data challenges in order to stay ahead of the curve.

Here are five core elements of a data strategy that organizations dealing with a large amount of data need to address:

Data Quality: Ensuring that the data being collected and stored is accurate, complete, and relevant can be a major challenge. Tools such as data quality software, data profiling, and data cleansing can help organizations improve the quality of their data and reduce the risk of errors and inconsistencies.
Here are some data quality tools:

Talend
Informatica Data Explorer
Trifacta Wrangler
MS SQL Server Data Quality Services (DQS)
SAP Information Steward
Redpoint

Data Integration: Combining data from multiple sources, both within and outside the organization, can be difficult. Tools such as data integration platforms and data warehousing solutions can help organizations manage and combine data from different sources in a consistent and efficient manner.
Here are some data integration tools:

Talend
Apache Kafka
Microsoft SSIS
CloverETL
Informatica PowerCenter
Striim
Oracle Data Integrator

Data Security: Protecting sensitive data from unauthorized access is critical for organizations. Tools such as encryption, access controls, and intrusion detection systems can help organizations secure their data and prevent potential breaches.
Here are some data security tools:

Endpoint Protection
Identity and Access Management
Data Loss Prevention
Multi-factor Authentication
Data Encryption

Data Governance: Ensuring that data is collected, stored, and used in a consistent and compliant manner can be a complex task. Tools such as data governance frameworks and data catalogs can help organizations establish clear policies and procedures and ensure that data is managed in a way that meets regulatory requirements.
Here are some data governance tools:

Collibra
Alation
Informatica Axon
Talend Data Governance
IBM InfoSphere
Data3Sixty
Ampool Moxie

Data Analytics: Making sense of large volumes of data and extracting valuable insights can be a challenge. Tools such as data visualization, machine learning, and artificial intelligence can help organizations analyze and interpret their data, and gain insights that can inform decision-making and drive business growth.
Here are some data analytics tools:

Tableau
PowerBI
MongoDB
Apache Spark
Hadoop
KNIME
SAS
Google Analytics

Overall, there are many tools available to help organizations overcome the challenges of managing enterprise data. By using these tools effectively, organizations can unlock the full potential of their data and use it to drive better decision-making and improved business outcomes.

e-Zest has been working collaboratively with its partners to chalk out the best fit/relevant Data Strategy to ensure alignment with Business Goals and Objectives whilst progressing on the Data maturity matrix. To know more write to us at info@e-zest.com or visit www.e-zest.com.

The Evolution of Data as an Asset

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