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The one thing that is common and transcends borders, companies, governments, geographies & human nature is, well yes – music and the arts, but what I want to talk about is the one thing that businesses have come to depend on increasingly in this day and age and that is DATA.

We heard a couple of decades ago or more that “Data was the new oil”. And that day when that was to be true has dawned well in the past. Today, data is the safe, and sane, foundation for all decisions – for example, whether it is retail stores deciding on where they place their wares, be it online or brick and mortar stores, whether it is Pharma companies distributing their inventory, whether it is infrastructure companies prioritising their tasks – all that logic is driven by data.

Data is the driver when it comes to making decisions that your enterprise’s future depends on. And data transcends all industries and has become prevalent in all interactions – how you treat your customers, your vendors, your partners, your employees, your branding & marketing, your go-to-market strategies, your view of emerging markets, your rebranding if required for that emerging market and your everything else.

When data is that important and crucial, it is important to acknowledge the monster that is very much lurking underneath and that monster is inaccurate, inconsistent and insufficient data!

In the data world, there are several problem statements that organisations and data professionals often deal with. Some of these are:

Data Quality: Ensuring the accuracy, consistency, completeness, and reliability of data. This includes addressing issues such as missing data, inconsistencies, duplications, and errors incurred while incorporating data from disparate data sources.

Data Integration: Combining and merging data from multiple sources, which may have different formats, structures, or standards. This aspect involves dealing with data transformation, data mapping, and resolving schema conflicts.

Data Security and Privacy: Protecting sensitive and confidential information from unauthorised access, breaches, or misuse. This includes implementing robust security measures, encryption, access controls, and complying with relevant & necessary, sometimes mandatory, data privacy regulations.

Data Governance: Establishing policies, processes, and frameworks to manage data assets effectively. This involves defining data ownership, roles and responsibilities, data standards, data lifecycle management, and ensuring compliance with regulatory requirements. In most B2C industries like BFSI, Gaming & Retail, this is especially important given we are dealing with direct customer data that is highly sensitive.

Data Storage and Scalability: Managing large volumes of data efficiently and effectively. This includes selecting appropriate storage technologies, designing scalable data architectures, optimising data retrieval and considering factors such as data partitioning and replication.

Data Analysis and Interpretation: Extracting insights, patterns, and meaningful information from data. This includes techniques such as data mining, statistical analysis, machine learning, and visualisation to make data-driven decisions.

Data Ethics and Bias: Addressing ethical considerations and potential biases in data collection, analysis, and interpretation, especially when dealing with a complex system of multiple applications. Ensuring fairness, transparency, and avoiding discrimination in algorithms and models that use data.

Data Access and Collaboration: Enabling seamless access to data for authorised users and facilitating collaboration among teams. This includes data sharing, data discovery, data cataloging, and implementing appropriate access controls.

Data Visualization and Communication: Effectively presenting data in a visual and understandable manner to facilitate comprehension and decision-making. This involves using charts, graphs, dashboards, and storytelling techniques. The tools that one chooses to use also have a bearing on what sort of intelligence one can glean from data.

Data Infrastructure and Technology: Selecting, implementing, and managing the right infrastructure, tools, and technologies to support data storage, processing, and analysis needs. This includes considerations for cloud computing, big data frameworks, data warehouses, and data pipelines.

These problem statements represent some of the key challenges in the data world, and organisations need to address them to leverage the full potential of their data assets.

Given how critical data is, every organisation needs to either have highly professional, proficient & productive teams, or they can simply outsource that whole responsibility to experts by partnering with eAppSys, whose sole business is to ensure organisations can optimally leverage their data which is maintained in its most pristine form, by our highly capable teams using our robust data management platform called DMOneTM Cloud!

Contact us at info@eappsys.com to know how you can have 10 less things to worry about.